problem solving with cognitive development

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Child cognitive development is a fascinating and complex process that entails the growth of a child’s mental abilities, including their ability to think, learn, and solve problems. This development occurs through a series of stages that can vary among individuals. As children progress through these stages, their cognitive abilities and skills are continuously shaped by a myriad of factors such as genetics, environment, and experiences. Understanding the nuances of child cognitive development is essential for parents, educators, and professionals alike, as it provides valuable insight into supporting the growth of the child’s intellect and overall well-being.

Throughout the developmental process, language and communication play a vital role in fostering a child’s cognitive abilities . As children acquire language skills, they also develop their capacity for abstract thought, reasoning, and problem-solving. It is crucial for parents and caregivers to be mindful of potential developmental delays, as early intervention can greatly benefit the child’s cognitive development. By providing stimulating environments, nurturing relationships, and embracing diverse learning opportunities, adults can actively foster healthy cognitive development in children.

Key Takeaways

• Child cognitive development involves the growth of mental abilities and occurs through various stages.
• Language and communication are significant factors in cognitive development , shaping a child’s ability for abstract thought and problem-solving.
• Early intervention and supportive environments can play a crucial role in fostering healthy cognitive development in children.

Child Cognitive Development Stages

Child cognitive development is a crucial aspect of a child’s growth and involves the progression of their thinking, learning, and problem-solving abilities. Swiss psychologist Jean Piaget developed a widely recognized theory that identifies four major stages of cognitive development in children.

Sensorimotor Stage

The Sensorimotor Stage occurs from birth to about 2 years old. During this stage, infants and newborns learn to coordinate their senses (sight, sound, touch, etc.) with their motor abilities. Their understanding of the world begins to develop through their physical interactions and experiences. Some key milestones in this stage include object permanence, which is the understanding that an object still exists even when it’s not visible, and the development of intentional actions.

Preoperational Stage

The Preoperational Stage takes place between the ages of 2 and 7 years old. In this stage, children start to think symbolically, and their language capabilities rapidly expand. They also develop the ability to use mental images, words, and gestures to represent the world around them. However, their thinking is largely egocentric, which means they struggle to see things from other people’s perspectives. During this stage, children start to engage in pretend play and begin to grasp the concept of conservation, recognizing that certain properties of objects (such as quantity or volume) remain the same even if their appearance changes.

Concrete Operational Stage

The Concrete Operational Stage occurs between the ages of 7 and 12 years old. At this stage, children’s cognitive development progresses to more logical and organized ways of thinking. They can now consider multiple aspects of a problem and better understand the relationship between cause and effect . Furthermore, children become more adept at understanding other people’s viewpoints, and they can perform basic mathematical operations and understand the principles of classification and seriation.

Formal Operational Stage

Lastly, the Formal Operational Stage typically begins around 12 years old and extends into adulthood. In this stage, children develop the capacity for abstract thinking and can consider hypothetical situations and complex reasoning. They can also perform advanced problem-solving and engage in systematic scientific inquiry. This stage allows individuals to think about abstract concepts, their own thought processes, and understand the world in deeper, more nuanced ways.

By understanding these stages of cognitive development, you can better appreciate the complex growth process that children undergo as their cognitive abilities transform and expand throughout their childhood.

Key Factors in Cognitive Development

Genetics and brain development.

Genetics play a crucial role in determining a child’s cognitive development. A child’s brain development is heavily influenced by genetic factors, which also determine their cognitive potential , abilities, and skills. It is important to understand that a child’s genes do not solely dictate their cognitive development – various environmental and experiential factors contribute to shaping their cognitive abilities as they grow and learn.

Environmental Influences

The environment in which a child grows up has a significant impact on their cognitive development. Exposure to various experiences is essential for a child to develop essential cognitive skills such as problem-solving, communication, and critical thinking. Factors that can have a negative impact on cognitive development include exposure to toxins, extreme stress, trauma, abuse, and addiction issues, such as alcoholism in the family.

Nutrition and Health

Maintaining good nutrition and health is vital for a child’s cognitive development. Adequate nutrition is essential for the proper growth and functioning of the brain . Key micronutrients that contribute to cognitive development include iron, zinc, and vitamins A, C, D, and B-complex vitamins. Additionally, a child’s overall health, including physical fitness and immunity, ensures they have the energy and resources to engage in learning activities and achieve cognitive milestones effectively .

Emotional and Social Factors

Emotional well-being and social relationships can also greatly impact a child’s cognitive development. A supportive, nurturing, and emotionally healthy environment allows children to focus on learning and building cognitive skills. Children’s emotions and stress levels can impact their ability to learn and process new information. Additionally, positive social interactions help children develop important cognitive skills such as empathy, communication, and collaboration.

In summary, cognitive development in children is influenced by various factors, including genetics, environmental influences, nutrition, health, and emotional and social factors. Considering these factors can help parents, educators, and policymakers create suitable environments and interventions for promoting optimal child development.

Language and Communication Development

Language skills and milestones.

Children’s language development is a crucial aspect of their cognitive growth. They begin to acquire language skills by listening and imitating sounds they hear from their environment. As they grow, they start to understand words and form simple sentences.

• Infants (0-12 months): Babbling, cooing, and imitating sounds are common during this stage. They can also identify their name by the end of their first year. Facial expressions play a vital role during this period, as babies learn to respond to emotions.
• Toddlers (1-3 years): They rapidly learn new words and form simple sentences. They engage more in spoken communication, constantly exploring their language environment.
• Preschoolers (3-5 years): Children expand their vocabulary, improve grammar, and begin participating in more complex conversations.

It’s essential to monitor children’s language development and inform their pediatrician if any delays or concerns arise.

Nonverbal Communication

Nonverbal communication contributes significantly to children’s cognitive development. They learn to interpret body language, facial expressions, and gestures long before they can speak. Examples of nonverbal communication in children include:

• Eye contact: Maintaining eye contact while interacting helps children understand emotions and enhances communication.
• Gestures: Pointing, waving goodbye, or using hand signs provide alternative ways for children to communicate their needs and feelings.
• Body language: Posture, body orientation, and movement give clues about a child’s emotions and intentions.

Teaching children to understand and use nonverbal communication supports their cognitive and social development.

Parent and Caregiver Interaction

Supportive interaction from parents and caregivers plays a crucial role in children’s language and communication development. These interactions can improve children’s language skills and overall cognitive abilities . Some ways parents and caregivers can foster language development are:

• Reading together: From an early age, reading books to children enhance their vocabulary and listening skills.
• Encouraging communication: Ask open-ended questions and engage them in conversations to build their speaking skills.
• Using rich vocabulary: Expose children to a variety of words and phrases, promoting language growth and understanding.

By actively engaging in children’s language and communication development, parents and caregivers can nurture cognitive, emotional, and social growth.

Cognitive Abilities and Skills

Cognitive abilities are the mental skills that children develop as they grow. These skills are essential for learning, adapting, and thriving in modern society. In this section, we will discuss various aspects of cognitive development, including reasoning and problem-solving, attention and memory, decision-making and executive function, as well as academic and cognitive milestones.

Reasoning and Problem Solving

Reasoning is the ability to think logically and make sense of the world around us. It’s essential for a child’s cognitive development, as it enables them to understand the concept of object permanence , recognize patterns, and classify objects. Problem-solving skills involve using these reasoning abilities to find solutions to challenges they encounter in daily life .

Children develop essential skills like:

• Logical reasoning : The ability to deduce conclusions from available information.
• Perception: Understanding how objects relate to one another in their environment.
• Schemes: Organizing thoughts and experiences into mental categories.

Attention and Memory

Attention refers to a child’s ability to focus on specific tasks, objects, or information, while memory involves retaining and recalling information. These cognitive abilities play a critical role in children’s learning and academic performance . Working memory is a vital component of learning, as it allows children to hold and manipulate information in their minds while solving problems and engaging with new tasks.

• Attention: Focuses on relevant tasks and information while ignoring distractions.
• Memory: Retains and retrieves information when needed.

Decision-Making and Executive Function

Decision-making is the process of making choices among various alternatives, while executive function refers to the higher-order cognitive processes that enable children to plan, organize, and adapt in complex situations. Executive function encompasses components such as:

• Inhibition: Self-control and the ability to resist impulses.
• Cognitive flexibility: Adapting to new information or changing circumstances.
• Planning: Setting goals and devising strategies to achieve them.

Academic and Cognitive Milestones

Children’s cognitive development is closely linked to their academic achievement. As they grow, they achieve milestones in various cognitive domains that form the foundation for their future learning. Some of these milestones include:

• Language skills: Developing vocabulary, grammar, and sentence structure.
• Reading and mathematics: Acquiring the ability to read and comprehend text, as well as understanding basic mathematical concepts and operations.
• Scientific thinking: Developing an understanding of cause-and-effect relationships and forming hypotheses.

Healthy cognitive development is essential for a child’s success in school and life. By understanding and supporting the development of their cognitive abilities, we can help children unlock their full potential and prepare them for a lifetime of learning and growth.

Developmental Delays and Early Intervention

Identifying developmental delays.

Developmental delays in children can be identified by monitoring their progress in reaching cognitive, linguistic, physical, and social milestones. Parents and caregivers should be aware of developmental milestones that are generally expected to be achieved by children at different ages, such as 2 months, 4 months, 6 months, 9 months, 18 months, 1 year, 2 years, 3 years, 4 years, and 5 years. Utilizing resources such as the “Learn the Signs. Act Early.” program can help parents and caregivers recognize signs of delay early in a child’s life.

Resources and Support for Parents

There are numerous resources available for parents and caregivers to find information on developmental milestones and to learn about potential developmental delays, including:

• Learn the Signs. Act Early : A CDC initiative that provides pdf checklists of milestones and resources for identifying delays.
• Parental support groups : Local and online communities dedicated to providing resources and fostering connections between families experiencing similar challenges.

Professional Evaluations and Intervention Strategies

If parents or caregivers suspect a developmental delay, it is crucial to consult with healthcare professionals or specialists who can conduct validated assessments of the child’s cognitive and developmental abilities. Early intervention strategies, such as the ones used in broad-based early intervention programs , have shown significant positive impacts on children with developmental delays to improve cognitive development and outcomes.

Professional evaluations may include:

• Pediatricians : Primary healthcare providers who can monitor a child’s development and recommend further assessments when needed.
• Speech and language therapists : Professionals who assist children with language and communication deficits.
• Occupational therapists : Experts in helping children develop or improve on physical and motor skills, as well as social and cognitive abilities.

Depending on the severity and nature of the delays, interventions may involve:

• Individualized support : Tailored programs or therapy sessions specifically developed for the child’s needs.
• Group sessions : Opportunities for children to learn from and interact with other children experiencing similar challenges.
• Family involvement : Parents and caregivers learning support strategies to help the child in their daily life.

Fostering Healthy Cognitive Development

Play and learning opportunities.

Encouraging play is crucial for fostering healthy cognitive development in children . Provide a variety of age-appropriate games, puzzles, and creative activities that engage their senses and stimulate curiosity. For example, introduce building blocks and math games for problem-solving skills, and crossword puzzles to improve vocabulary and reasoning abilities.

Playing with others also helps children develop social skills and better understand facial expressions and emotions. Provide opportunities for cooperative play, where kids can work together to achieve a common goal, and open-ended play with no specific rules to boost creativity.

Supportive Home Environment

A nurturing and secure home environment encourages healthy cognitive growth. Be responsive to your child’s needs and interests, involving them in everyday activities and providing positive reinforcement. Pay attention to their emotional well-being and create a space where they feel safe to ask questions and explore their surroundings.

Promoting Independence and Decision-Making

Support independence by allowing children to make decisions about their playtime, activities, and daily routines. Encourage them to take age-appropriate responsibilities and make choices that contribute to self-confidence and autonomy. Model problem-solving strategies and give them opportunities to practice these skills during play, while also guiding them when necessary.

Healthy Lifestyle Habits

Promote a well-rounded lifestyle, including:

• Sleep : Ensure children get adequate and quality sleep by establishing a consistent bedtime routine.
• Hydration : Teach the importance of staying hydrated by offering water frequently, especially during play and physical activities.
• Screen time : Limit exposure to electronic devices and promote alternative activities for toddlers and older kids.
• Physical activity : Encourage children to engage in active play and exercise to support neural development and overall health .

Frequently Asked Questions

What are the key stages of child cognitive development.

Child cognitive development can be divided into several key stages based on Piaget’s theory of cognitive development . These stages include the sensorimotor stage (birth to 2 years), preoperational stage (2-7 years), concrete operational stage (7-11 years), and formal operational stage (11 years and beyond). Every stage represents a unique period of cognitive growth, marked by the development of new skills, thought processes, and understanding of the world.

What factors influence cognitive development in children?

Several factors contribute to individual differences in child cognitive development, such as genetic and environmental factors. Socioeconomic status, access to quality education, early home environment, and parental involvement all play a significant role in determining cognitive growth. In addition, children’s exposure to diverse learning experiences, adequate nutrition, and mental health also influence overall cognitive performance .

How do cognitive skills vary during early childhood?

Cognitive skills in early childhood evolve as children progress through various stages . During the sensorimotor stage, infants develop fundamental skills such as object permanence. The preoperational stage is characterized by the development of symbolic thought, language, and imaginative play. Children then enter the concrete operational stage, acquiring the ability to think logically and solve problems. Finally, in the formal operational stage, children develop abstract reasoning abilities, complex problem-solving skills and metacognitive awareness.

What are common examples of cognitive development?

Examples of cognitive development include the acquisition of language and vocabulary, the development of problem-solving skills, and the ability to engage in logical reasoning. Additionally, memory, attention, and spatial awareness are essential aspects of cognitive development. Children may demonstrate these skills through activities like puzzle-solving, reading, and mathematics.

How do cognitive development theories explain children’s learning?

Piaget’s cognitive development theory suggests that children learn through active exploration, constructing knowledge based on their experiences and interactions with the world. In contrast, Vygotsky’s sociocultural theory emphasizes the role of social interaction and cultural context in learning. Both theories imply that cognitive development is a dynamic and evolving process, influenced by various environmental and psychological factors.

Why is it essential to support cognitive development in early childhood?

Supporting cognitive development in early childhood is critical because it lays a strong foundation for future academic achievement, social-emotional development, and lifelong learning. By providing children with diverse and enriching experiences, caregivers and educators can optimize cognitive growth and prepare children to face the challenges of today’s complex world. Fostering cognitive development early on helps children develop resilience, adaptability, and critical thinking skills essential for personal and professional success.

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What Is Cognitive Development? 3 Psychology Theories

But don’t worry, we will try our best to help you with the essentials of this complex field of study.

We’ll start with some background, then show you how cognitive skills are used every day. In addition, we will explain a few theories and describe fascinating studies.

Since cognitive development goes beyond childhood and into adolescence, we are sure you will want to know all about this, too.

To end this article, we provide some helpful resources. You can use these to support the cognitive skills of your students or clients.

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This Article Contains:

What is cognitive development in psychology, cognitive development skills & important milestones, 5 real-life examples of cognitive development, 3 ground-breaking cognitive development theories, a look at cognitive development in adolescence, 3 fascinating research studies, helpful resources from positivepsychology.com, a take-home message.

Cognitive development is how humans acquire, organize, and learn to use knowledge (Gauvain & Richert, 2016).

In psychology, the focus of cognitive development has often been only on childhood. However, cognitive development continues through adolescence and adulthood. It involves acquiring language and knowledge, thinking, memory, decision making, problem solving, and exploration (Von Eckardt, 1996).

Much of the research within cognitive development in children focuses on thinking, developing knowledge, exploring, and solving problems (Carpendale & Lewis, 2015).

Nature vs nurture debate

The nature versus nurture debate refers to how much an individual inherits compared to how much they are influenced by the environment. How do nature and nurture shape cognitive development?

American psychologist Arthur Jensen (1969, 1974) emphasized the role of genetics within intelligence, arguing for a genetic difference in the intelligence of white and Black people.

Jensen (1969) made some very bold assertions, stating that Black people have lower cognitive abilities. His research was heavily criticized for being discriminatory. He did not consider the inbuilt bias of psychometric testing (Ford, 1996). The lower test scores of Black individuals were more likely to be a result of a lack of resources and poor-quality life opportunities (Ford, 2004).

In an enormous cross-sample of 11,000 adolescent twins, Brant et al. (2013) found that those with a higher intelligence quotient (IQ) appeared to be more influenced by nurture and stimulation. The researchers suggested this may be because of their heightened attention and arousal system, absorbing more information from the environment, being more open to new experiences, and allowing brain plasticity and changes to occur.

They also found that adolescents with a lower IQ showed more genetic influence on their IQ from their parents. The researchers suggested that their lower levels of intelligence may result in lower motivation levels and an inability to seek out new experiences.

This study highlights the need for those with lower IQ levels to be supported with positive interventions to increase their cognitive abilities and capacity.

These milestones reflect skill achievement and take into account genetic makeup and environmental influence (Dosman, Andrews, & Goulden, 2012).

Here are a few of these important milestones, the associated skills, and the age at which they are typically achieved. The following table is modified from the Child Development Institute .

Table 1. Children’s cognitive milestones and skill development

Language and other cognitive skills

Language skills are essential for a child’s ability to communicate and engage with others. These skills support other areas of a child’s development, such as cognitive, literacy, and social development (Roulstone, Loader, Northstone, & Beveridge, 2002).

The modified table below was sourced from the Australian parenting website raisingchildren.net.au and describes how language develops in children.

Table 2. Language development from 0 to 8 years

Thinking skills

Thinking concerns manipulating information and is related to reasoning, decision making, and problem solving (Kashyap & Minda, 2016). It is required to develop language, because you need words to think.

Cognitive development activities helps thinking and reasoning to grow. Thinking is a skill that does not commence at birth. It develops gradually through childhood and advances more rapidly when children are around two years old. Reasoning develops around six. By the time they’re 11, children’s thinking becomes much more abstract and logical (Piaget, 1936).

Developing knowledge

Knowledge is essential for cognitive development and academic achievement. Increased knowledge equates to better speaking, reading, listening, and reasoning skills. Knowledge is not only related to language. It can also be gained by performing a task (Bhatt, 2000). It starts from birth as children begin to understand the world around them through their senses (Piaget, 1951).

Building knowledge is important for children to encode and retrieve new information. This makes them able to learn new material. Knowledge helps to facilitate critical thinking (Piaget, 1936). Clearly, the development of children’s knowledge base is a critical part of cognitive development.

Memory development

The development of memory is lifelong and related to personal experiences.

Explicit memory, which refers to remembering events and facts of everyday life, develops in the first two years (Stark, Yassa, & Stark, 2010). Explicit memory develops around 8 to 10 months.

Working memory and its increase in performance can be seen from three to four years through adolescence (Ward, Berry, & Shanks, 2013). This is demonstrated through increased attention, the acquisition of language, and increased knowledge.

Implicit memory, which is unconscious and unintentional, is an early developing memory system in infants and develops as the brain matures (Ward et al., 2013).

Perceptual skills

Perceptual skills develop from birth. They are an important aspect of cognitive development. Most children are born with senses of sight, hearing, touch, taste, and smell (Karasik, Tamis-LeMonda, & Adolph, 2014).

As children develop, they learn to communicate by interacting with their environment and using their sensory and motor skills (Karasik et al., 2014).

When visual, tactile, and auditory skills are combined, they emerge as perceptual skills. These perceptual skills are then used to gauge spatial relationships, discriminate between figure and ground, and develop hand–eye coordination (Libertus & Hauf, 2017).

Exploring and solving problems

Problem solving can be seen in very young children when they play with blocks, objects, and balls. It is entwined with perceptual skills and memory. Very young children playing with blocks, picking up a spoon, or even looking for objects demonstrate the development of problem solving skills (Goldschmied & Jackson, 1994). This is known as heuristic play (Auld, 2002).

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To understand how people think and process information, it is important to look at how cognitive skills are used in everyday life. Here are some real-life examples of cognitive development.

Decision making

To make a decision, a person needs to weigh up information and make the best choice. As an example, think about a restaurant menu. There is a lot of information on the menu about food options. Reading the menu requires you to analyze the data then reduce it to make a specific meal choice.

Recognition of faces

Have you ever wondered why it is possible to recognize a person even when they have grown a beard, wear makeup or glasses, or change their hair color?

Cognitive processing is used in facial recognition and explains why we still recognize people we meet after a long time, despite sometimes drastic changes in their physical appearance.

Cognitive-Behavioral Therapy (CBT)

This widely used therapeutic intervention is based on an understanding of cognition and how it changes behavior.

It is based on the premise that cognition and behavior are linked, and this theory is often used to help individuals overcome negative thinking patterns . CBT provides them with alternative positive thinking patterns to promote positive behavior.

The cognitive processes of short-term and long-term memory explain forgetting. An example of forgetting can be seen in students who do not study for exams. If they do not transfer the information from short-term to long-term memory, they forget the knowledge required for the examination and may fail.

Thinking and cognition are required for reasoning. Reasoning involves intellect and an attempt to search for the truth from new or existing information. An example of this activity can be seen in political debates on television.

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There are several cognitive development theories, some more well known than others.

They all attempt to explain how cognitive development occurs.

Piaget’s cognitive development theory

The sensorimotor stage (0–2 years) is when infants build an understanding of the world through their senses and movement (touching, feeling, listening, and watching). This is when children develop object permanence.

The pre-operational stage (2–7 years) is when language and abstract thinking arise. This is the stage of symbolic play.

When a child is 7 years old, they enter Piaget’s concrete-operational stage , which goes up to 11 years. This is when logical and concrete thought come into action.

At the age of 11 onward, children learn logical and abstract rules and solve problems. Piaget described this as the formal operational stage.

Vygotsky’s theory

Lev Vygotsky described an alternative theory. He believed that children’s cognitive development arises through their physical interaction with the world (Vygotsky, 1932). Vygotsky’s theory is based on the premise that the support of adults and peers enables the development of higher psychological functions. His is known as the sociocultural theory (Yasnitsky, 2018).

Vygotsky believed that a child’s initial social interactions prompt development, and as the child internalizes learning, this shifts their cognition to an individual level.

Vygotsky (1932) considered children akin to apprentices, learning from the more experienced, who understand their needs.

There are two main themes of Vygotsky’s theory.

The zone of proximal development is described as the distance between the actual development level and the level of potential. This is determined by independent problem solving when children are collaborating with more able peers or under the guidance of an adult (Vygotsky, 1931).

This may explain why some children perform better in the presence of others who have more knowledge and skills but more poorly on their own. These skills, displayed in a social context but not in an isolated setting, are within the zone of proximal development. This highlights how a more knowledgeable person can provide support to a child’s cognitive development (Vygotsky, 1932).

Thinking and speech are considered essential. Vygotsky described a connected relationship between language development and the thinking process. His theory explains how younger children use speech to think out loud. Gradually, they evolve silent inner speech once mental concepts and cognitive awareness are developed (Vygotsky, 1931).

Ecological systems theory

Another more modern theory, similar in some sense to Vygotsky’s, is one by American psychologist Urie Bronfenbrenner (1974). He suggested that a child’s environment, within an arrangement of structures, has a differing impact on the child (Bronfenbrenner, 1974).

Bronfenbrenner’s five structures are the micro-system, mesosystem, ecosystem, macrosystem, and chronosystem. These concern the surrounding environment, family, school, values, customs, and cultures. They are interrelated, with each system influencing others to impact the child’s development (Bronfenbrenner, 1977).

Bronfenbrenner (1974) considered the micro-system as the most influential. This system contains the developing child, family, and educational environment, and impacts a child’s cognitive development the most.

Piaget’s theory of cognitive development – Sprouts

Adolescence is a period of transition between late childhood and the beginning of adulthood.

Based on Inhelder and Piaget’s (1958) stage theory of cognitive growth, adolescence is when children become self-conscious and concerned with other people’s opinions as they go through puberty (Steinberg, 2005). The psychosocial context of adolescents is considerably different from that of children and adults.

The brain goes through a dramatic remodeling process in adolescence. Neural plasticity facilitates the development of social cognitive skills (Huttenlocher, 1979). Structural development of cortical regions of the brain may significantly influence cognitive functioning during adolescence (Huttenlocher, De Courten, Garey, & Van der Loos, 1983).

Recognition of facial expressions and emotion is one area of social cognition that has been investigated in adolescence (Herba & Phillips, 2004). The amygdala, a part of the brain associated with emotion processing, was found to be significantly activated in response to fearful facial expressions in a study of adolescents (Baird et al., 1999). This highlights that the development of emotional cognition is prominent in this age group.

Here are three we find most interesting.

1. A cognitive habilitation program for children

Millians and Coles (2014) studied five children who had experienced learning and academic deficits because of prenatal alcohol exposure. Before and after an intervention, researchers gave standardized tests of nonverbal reasoning and academic achievement to the children.

Four of the five children showed increases to the average range of scores on measures of nonverbal, reasoning, reading, and mathematics. This study highlighted the benefit of interventions to address children’s cognitive difficulties and learning problems, even when the cognitive difficulties are apparent from birth.

2. Bilingual babies and enhanced learning

Introducing babies to two languages has been shown to improve cognitive abilities, especially problem solving (Ramírez-Esparza, García-Sierra, & Kuhl, 2017).

Spanish babies between 7 and 33.5 months were given one hour of English sessions for 18 weeks. By the end of the 18 weeks, the children produced an average of 74 English words and phrases. This study showed that the age between 0 and 3 years is the best time to learn a second language and gain excellent proficiency. However, languages can be learned at any time in life.

3. Unusual autobiographical memory

In an unusual case study, a woman described as ‘AJ’ was found to have highly superior autobiographical memory, a condition that dominated her life (Parker, Cahill, & McGaugh, 2006).

Her memory was described as ‘nonstop, uncontrollable and automatic.’ AJ did not use any mnemonic devices to recall. She could tell you what she was doing on any day of her life.

AJ could also recall her past with a high level of accuracy. This study provided some insightful details of the neurobiology of autobiographical memory and changes in the prefrontal cortex that cause these superior cognitive abilities.

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If this article has piqued your interest and you wish to know more about improving cognitive function, take a look at these related posts.

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Alongside exercise, sleep is an essential component for the brain to function properly. This article has excellent sleep hygiene ideas , and you can use the checklists and worksheets to support your clients’ sleep, enabling them to boost their brain functioning.

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The first few years of a child’s life show rapid changes in brain development. This is part of the child’s cognitive development. There are a number of different theories of how and when this occurs. These are not set in stone, but are a guide to the cognitive development of children.

If children are not achieving their milestones at the approximate times they should, extra support can help make a difference. Even children with fetal alcohol syndrome can achieve considerably improved cognition with specialized support.

Remember, cognitive development does not end in childhood, as Piaget’s schema theory first suggested. It continues through adolescence and beyond. Cognitive development changes carry on through much of a teenager’s life as the brain is developing.

We hope you enjoyed reading this article. Don’t forget to download our three Positive Psychology Exercises for free .

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Cognitive Development Theory: What Are the Stages?

Sensorimotor stage, preoperational stage, concrete operational stage, formal operational stage.

Cognitive development is the process by which we come to acquire, understand, organize, and learn to use information in various ways. Cognitive development helps a child obtain the skills needed to live a productive life and function as an independent adult.

The late Swiss psychologist Jean Piaget was a major figure in the study of cognitive development theory in children. He believed that it occurs in four stages—sensorimotor, preoperational, concrete operational, and formal operational.

This article discusses Piaget’s stages of cognitive development, including important concepts and principles.

FatCamera / Getty Images

History of Cognitive Development

During the 1920s, the psychologist Jean Piaget was given the task of translating English intelligence tests into French. During this process, he observed that children think differently than adults do and have a different view of the world. He began to study children from birth through the teenage years—observing children who were too young to talk, and interviewing older children while he also observed their development.

Piaget published his theory of cognitive development in 1936. This theory is based on the idea that a child’s intelligence changes throughout childhood and cognitive skills—including memory, attention, thinking, problem-solving, logical reasoning, reading, listening, and more—are learned as a child grows and interacts with their environment.

Stages of Cognitive Development

Piaget’s theory suggests that cognitive development occurs in four stages as a child ages. These stages are always completed in order, but last longer for some children than others. Each stage builds on the skills learned in the previous stage.

The four stages of cognitive development include:

• Sensorimotor
• Preoperational
• Concrete operational
• Formal operational

The sensorimotor stage begins at birth and lasts until 18 to 24 months of age. During the sensorimotor stage, children are physically exploring their environment and absorbing information through their senses of smell, sight, touch, taste, and sound.

The most important skill gained in the sensorimotor stage is object permanence, which means that the child knows that an object still exists even when they can't see it anymore. For example, if a toy is covered up by a blanket, the child will know the toy is still there and will look for it. Without this skill, the child thinks that the toy has simply disappeared.

Language skills also begin to develop during the sensorimotor stage.

Activities to Try During the Sensorimotor Stage

Appropriate activities to do during the sensorimotor stage include:

• Playing peek-a-boo
• Reading books
• Providing toys with a variety of textures
• Singing songs
• Playing with musical instruments
• Rolling a ball back and forth

The preoperational stage of Piaget's theory of cognitive development occurs between ages 2 and 7 years. Early on in this stage, children learn the skill of symbolic representation. This means that an object or word can stand for something else. For example, a child might play "house" with a cardboard box.

At this stage, children assume that other people see the world and experience emotions the same way they do, and their main focus is on themselves. This is called egocentrism .

Centrism is another characteristic of the preoperational stage. This means that a child is only able to focus on one aspect of a problem or situation. For example, a child might become upset that a friend has more pieces of candy than they do, even if their pieces are bigger.

During this stage, children will often play next to each other—called parallel play—but not with each other. They also believe that inanimate objects, such as toys, have human lives and feelings.

Activities to Try During the Preoperational Stage

Appropriate activities to do during the preoperational stage include:

• Playing "house" or "school"
• Building a fort
• Playing with Play-Doh
• Building with blocks
• Playing charades

The concrete operational stage occurs between the ages of 7 and 11 years. During this stage, a child develops the ability to think logically and problem-solve but can only apply these skills to objects they can physically see—things that are "concrete."

Six main concrete operations develop in this stage. These include:

• Conservation : This skill means that a child understands that the amount of something or the number of a particular object stays the same, even when it looks different. For example, a cup of milk in a tall glass looks different than the same amount of milk in a short glass—but the amount did not change.
• Classification : This skill is the ability to sort items by specific classes, such as color, shape, or size.
• Seriation : This skill involves arranging objects in a series, or a logical order. For example, the child could arrange blocks in order from smallest to largest.
• Reversibility : This skill is the understanding that a process can be reversed. For example, a balloon can be blown up with air and then deflated back to the way it started.
• Decentering : This skill allows a child to focus on more than one aspect of a problem or situation at the same time. For example, two candy bars might look the same on the outside, but the child knows that they have different flavors on the inside.
• Transitivity : This skill provides an understanding of how things relate to each other. For example, if John is older than Susan, and Susan is older than Joey, then John is older than Joey.

Activities to Try During the Concrete Operational Stage

Appropriate activities to do during the concrete operational stage include:

• Using measuring cups (for example, demonstrate how one cup of water fills two half-cups)
• Solving simple logic problems
• Practicing basic math
• Doing crossword puzzles
• Playing board games

The last stage in Piaget's theory of cognitive development occurs during the teenage years into adulthood. During this stage, a person learns abstract thinking and hypothetical problem-solving skills.

Deductive reasoning—or the ability to make a conclusion based on information gained from a person's environment—is also learned in this stage. This means, for example, that a person can identify the differences between dogs of various breeds, instead of putting them all in a general category of "dogs."

Activities to Try During the Formal Operational Stage

Appropriate activities to do during the formal operational stage include:

• Learning to cook
• Solving crossword and logic puzzles
• Exploring hobbies
• Playing a musical instrument

Piaget's theory of cognitive development is based on the belief that a child gains thinking skills in four stages: sensorimotor, preoperational, concrete operational, and formal operational. These stages roughly correspond to specific ages, from birth to adulthood. Children progress through these stages at different paces, but according to Piaget, they are always completed in order.

National Library of Medicine. Cognitive testing . MedlinePlus.

Oklahoma State University. Cognitive development: The theory of Jean Piaget .

SUNY Cortland. Sensorimotor stage .

Marwaha S, Goswami M, Vashist B. Prevalence of principles of Piaget’s theory among 4-7-year-old children and their correlation with IQ . J Clin Diagn Res. 2017;11(8):ZC111-ZC115. doi:10.7860%2FJCDR%2F2017%2F28435.10513

Börnert-Ringleb M, Wilbert J. The association of strategy use and concrete-operational thinking in primary school . Front Educ. 2018;0. doi:10.3389/feduc.2018.00038

By Aubrey Bailey, PT, DPT, CHT Dr, Bailey is a Virginia-based physical therapist and professor of anatomy and physiology with over a decade of experience.

• Vygotsky’s Theory of Cognitive Development

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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Sociocultural Theory 

The work of Lev Vygotsky (1934, 1978) has become the foundation of much research and theory in cognitive development over the past several decades, particularly what has become known as sociocultural theory.

Vygotsky’s theory comprises concepts such as culture-specific tools, private speech, and the zone of proximal development.

Vygotsky believed cognitive development is influenced by cultural and social factors. He emphasized the role of social interaction in the development of mental abilities e.g., speech and reasoning in children.

Vygotsky strongly believed that community plays a central role in the process of “making meaning.”

Cognitive development is a socially mediated process in which children acquire cultural values, beliefs, and problem-solving strategies through collaborative dialogues with more knowledgeable members of society.

The more knowledgeable other (MKO) is someone who has a higher level of ability or greater understanding than the learner regarding a particular task, process, or concept.

The MKO can be a teacher, parent, coach, or even a peer who provides guidance and modeling to enable the child to learn skills within their zone of proximal development (the gap between what a child can do independently and what they can achieve with guidance).

The interactions with more knowledgeable others significantly increase not only the quantity of information and the number of skills a child develops, but also affects the development of higher-order mental functions such as formal reasoning. Vygotsky argued that higher mental abilities could only develop through interaction with more advanced others.

According to Vygotsky, adults in society foster children’s cognitive development by engaging them in challenging and meaningful activities. Adults convey to children how their culture interprets and responds to the world.

They show the meaning they attach to objects, events, and experiences. They provide the child with what to think (the knowledge) and how to think (the processes, the tools to think with).

Vygotsky’s theory encourages collaborative and cooperative learning between children and teachers or peers. Scaffolding and reciprocal teaching are effective educational strategies based on Vygotsky’s ideas.

Scaffolding involves the teacher providing support structures to help students master skills just beyond their current level. In reciprocal teaching, teachers and students take turns leading discussions using strategies like summarizing and clarifying. Both scaffolding and reciprocal teaching emphasize the shared construction of knowledge, in line with Vygotsky’s views.

Vygotsky highlighted the importance of language in cognitive development. Inner speech is used for mental reasoning, and external speech is used to converse with others.

Initially, these operations occur separately. Indeed, before age two, a child employs words socially; they possess no internal language.

Once thought and language merge, however, the social language is internalized and assists the child with their reasoning. Thus, the social environment is ingrained within the child’s learning.

Effects of Culture

Vygotsky’s theory emphasizes individuals’ active role in their cognitive development, highlighting the interplay between innate abilities, social interaction, and cultural tools.

Vygotsky posited that people aren’t passive recipients of knowledge but actively interact with their environment. This interaction forms the basis of cognitive development.

Infants are born with basic abilities for intellectual development, called “elementary mental functions.” These include attention, sensation, perception, and memory.

Through interaction within the sociocultural environment, elementary functions develop into more sophisticated “higher mental functions.”

Higher mental functions are advanced cognitive processes that develop through social interaction and cultural influences. They are distinct from the basic, innate elementary mental functions.

Unlike elementary functions (like basic attention or memory), higher functions are:

• Conscious awareness : The individual is aware of these processes.
• Voluntary control : They can be deliberately used and controlled.
• Mediated : They involve the use of cultural tools or signs (like language).
• Social in origin : They develop through social interaction.

Examples include language and communication, logical reasoning, problem-solving, planning, attention control, self-regulation, and metacognition.

Vygotsky posited that higher mental functions are not innate but develop through social interaction and the internalization of cultural tools.

Tools of Intellectual Adaptation

Cultural tools are methods of thinking and problem-solving strategies that children internalize through social interactions with more knowledgeable members of society.

These tools, such as language, counting systems, mnemonic techniques, and art forms, shape the way individuals think, problem-solve, and interact with the world.

Tools of intellectual adaptation is Vygotsky’s term for methods of thinking and problem-solving strategies that children internalize through social interactions with the more knowledgeable members of society.

Cultural tools, particularly language, influence the development of higher-order thinking skills.

Other tools include writing systems, number systems, mnemonic techniques, works of art, diagrams, maps, and drawings.

These tools are products of sociocultural evolution, passed down and transformed across generations.

Each culture provides its children with tools of intellectual adaptation that allow them to use basic mental functions more effectively.

These tools, along with social interaction, contribute to the development of higher mental functions through a process of internalization.

This historical and cultural embeddedness means that tools carry within them the accumulated knowledge and practices of a particular community.

For example, biological factors limit memory in young children. However, culture determines the type of memory strategy we develop.

For example, in Western culture, children learn note-taking to aid memory, but in pre-literate societies, other strategies must be developed, such as tying knots in a string to remember, carrying pebbles, or repeating the names of ancestors until large numbers can be repeated.

Vygotsky, therefore, sees cognitive functions, even those carried out alone, as affected by the beliefs, values, and tools of intellectual adaptation of the culture in which a person develops and, therefore, socio-culturally determined.

Therefore, intellectual adaptation tools vary from culture to culture – as in the memory example.

More Knowledgeable Other

The more knowledgeable other (MKO) is somewhat self-explanatory; it refers to someone who has a better understanding or higher skill level than the learner in a particular task or concept.

As a result of shared dialogues with more knowledgeable others, which provide hints, instructions, and encouragement, the child can internalize the ‘how to do it’ part of the task as part of their inner or private speech. The child can use this later when they tackle a similar task independently.

Although the implication is that the MKO is a teacher or an older adult, this is not necessarily the case. Often, a child’s peers or an adult’s children may be the individuals with more knowledge or experience.

What constitutes “more knowledgeable” can vary across cultures and contexts. In some situations, traditional knowledge held by elders might be most valued, while in others, cutting-edge technical skills of younger individuals might be more relevant.

For example, who is more likely to know more about the newest teenage music groups, how to win at the most recent PlayStation game, or how to correctly perform the newest dance craze – a child or their parents?

In fact, the MKO need not be a person at all. To support employees in their learning process, some companies are now using electronic performance support systems.

Electronic tutors have also been used in educational settings to facilitate and guide students through learning. The key to MKOs is that they must have (or be programmed with) more knowledge about the topic being learned than the learner does.

The MKO is not a static position of superiority but a fluid role that shifts contextually in response to the learners’ evolving understanding and the dynamics of the learning environment.

As learners gain greater understanding, they can transition from being novices to assuming the role of MKO for their peers.

This highlights the collaborative and fluid nature of learning within the ZPD, where knowledge is co-constructed rather than simply transmitted from a more knowledgeable individual.

Abtahi (2016) suggests that tools themselves can function as “more knowledgeable others,” embodying cultural-historical knowledge that guides learners’ thinking and actions.

Abtahi uses the example of fraction strips guiding children’s understanding of fraction addition, even without direct instruction from an adult. This suggests that the design and affordances of tools can structure learning experiences, creating a zone of proximal development (ZPD) where learners, through their interactions with these tools, can achieve more than they could independently.

This idea is further supported by Puntambekar and Hübscher (2005), who discuss the use of curricula, software tools, and other resources as forms of scaffolding.

Zone of Proximal Development

The concept of the more knowledgeable other relates to the second important principle of Vygotsky’s work, the zone of proximal development (ZPD).

The ZPD relates to the difference between what a child (or a novice) can achieve independently and what a child can achieve with guidance and encouragement from a skilled partner.

Vygotsky (1978) views the zone of proximal development as the area where the most sensitive instruction or guidance should occur, enabling the child to develop skills they will later use independently, thus fostering higher mental functions.

The ZPD is not a static space but constantly shifts as the child learns and develops new skills. As a child’s competence grows, their zone of proximal development also expands to encompass new challenges.

Vygotsky emphasizes social interaction as crucial to learning, arguing that children develop more fully with support than alone. He defines the gap between actual and potential learning as the ZPD, asserting that collaboration with more knowledgeable others is essential to bridge this gap.

According to Vygotsky (1978), the child (or a novice) learns through social interaction with a skillful tutor. The tutor may model behaviors and/or provide verbal instructions for the child.

Vygotsky refers to this as cooperative or collaborative dialogue. The child seeks to understand the actions or instructions provided by the tutor (often the parent or teacher) and then internalizes the information, using it to guide or regulate their performance.

Social interaction, therefore, supports the child’s cognitive development in the ZPD, leading to a higher level of reasoning. 

Internalization of Knowledge

Internalization is a central concept in Vygotsky’s theory, bridging the gap between social interaction and individual cognitive development.

It’s the process by which external, socially mediated activities are transformed into internal mental processes, allowing individuals to acquire new knowledge and skills.

Vygotsky viewed higher mental functions, such as language, reasoning, and self-regulation, as originating in social interaction. He argued that these functions are not innate or biologically determined but acquired through participation in culturally meaningful activities with others.

Internalization within the ZPD isn’t a passive transfer of information but a dynamic process where learners actively participate and engage in meaning-making.

This active engagement ensures that learners don’t simply replicate the expert’s actions but develop a deeper understanding of the underlying principles and strategies.

For example, a child learning to solve a problem with a parent’s guidance doesn’t simply memorize the solution but actively constructs their understanding through dialogue and interaction .

This process, often termed scaffolding, underscores the importance of providing support that aligns with the learner’s current capabilities and gradually diminishes as the learner gains mastery.

Scaffolding

The ZPD has become synonymous with the term “scaffolding” in the literature. However, it is important to note that Vygotsky never used this term in his writing; it was introduced by Wood, Bruner, and Ross (1976).

Scaffolding consists of activities provided by the educator or a more knowledgeable person to support the student as he or she is led through the zone of proximal development.

It’s the “how” of guided learning, the specific strategies and techniques used by a more knowledgeable other to bridge the gap between a learner’s current abilities and potential development.

This support can be provided in many different ways, such as modeling or asking questions, and is used across different subjects and age groups.

Scaffolding is a dynamic process that changes based on the student’s progress and the task at hand, so it will look different in different situations.

Contingency (or responsiveness) is paramount. This means the teacher continually assesses the learner’s understanding and calibrates their support accordingly.

Support is tapered off (i.e., withdrawn) as it becomes unnecessary, much as a scaffold is removed from a building during construction. The student will then be able to complete the task again independently.

Shaffer (1996) gives the example of a young girl given her first jigsaw. Alone, she performs poorly in attempting to solve the puzzle. The father then sits with her and describes or demonstrates some basic strategies, such as finding all the corner/edge pieces, and provides a couple of pieces for the child to put together herself, and offers encouragement when she does so.

As the child becomes more competent, the father allows the child to work more independently. 

Evidence for Vygotsky and the ZPD

Freund (1990) conducted a study in which children had to decide which furniture items should be placed in particular areas of a doll’s house.

Some children were allowed to play with their mother in a similar situation before they attempted it alone (zone of proximal development) while others were allowed to work on this by themselves (Piaget’s discovery learning).

Freund found that those who had previously worked with their mother (ZPD) showed the greatest improvement compared with their first attempt at the task.

The conclusion is that guided learning within the ZPD led to greater understanding/performance than working alone (discovery learning).

Vygotsky and Language

Vygotsky believed that language develops from social interactions for communication purposes. Vygotsky viewed language as man’s greatest tool for communicating with the outside world.

According to Vygotsky (1962), language plays two critical roles in cognitive development:

• Cultural transmission of knowledge : Language is the primary vehicle for passing down cultural knowledge, values, and practices across generations. This transmission occurs through formal instruction and informal interactions, shaping individuals’ understanding of the world and their place within it.
• Language becomes a powerful tool for intellectual adaptation : Language is not merely a tool for communication; it’s a tool for thinking. Language facilitates the development of higher mental functions like abstract thinking, planning, and problem-solving.

Vygotsky (1987) differentiates between three forms of language:

• Social speech: The initial form of language serves as the primary means for children to engage with others, establish shared meanings, and participate in cultural activities (typical from age two).
• Private speech: Overt and audible speech directed to the self and serves an intellectual function (typical from age three).
• Inner speech: According to Vygotsky, private speech doesn’t simply disappear; it goes “underground,” transforming into silent inner speech (typical from age seven).

For Vygotsky, thought and language are initially separate systems from the beginning of life, merging at around three years of age.

At this point, speech and thought become interdependent: thought becomes verbal, and speech becomes representational.

As children develop mental representation, particularly the skill of language, they start to communicate with themselves in much the same way as they would communicate with others.

When this happens, children’s monologues are internalized to become inner speech. The internalization of language is important as it drives cognitive development.

This internal dialogue allows individuals to mentally rehearse different viewpoints, contributing to more sophisticated social understanding and problem-solving abilities.

“Inner speech is not the interiour aspect of external speech – it is a function in itself. It still remains speech, i.e., thought connected with words. But while in external speech thought is embodied in words, in inner speech words dies as they bring forth thought. Inner speech is to a large extent thinking in pure meanings.” (Vygotsky, 1962: p. 149)

Private Speech

Vygotsky (1987) was the first psychologist to document the importance of private speech.

He considered private speech as the transition point between social and inner speech, the moment in development where language and thought unite to constitute verbal thinking.

Thus, in Vygotsky’s view, private speech was the earliest manifestation of inner speech. Indeed, private speech is more similar (in form and function) to inner speech than social speech.

Private speech is “typically defined, in contrast to social speech, as speech addressed to the self (not to others) for the purpose of self-regulation (rather than communication).” (Diaz, 1992, p.62)

Private speech is overt, audible, and observable, often seen in children who talk to themselves while problem-solving.

Conversely, inner speech is covert or hidden because it happens internally. It is the silent, internal dialogue that adults often engage in while thinking or problem-solving.

In contrast to Piaget’s (1959) notion of private speech representing a developmental dead-end, Vygotsky (1934, 1987) viewed private speech as:

“A revolution in development which is triggered when preverbal thought and preintellectual language come together to create fundamentally new forms of mental functioning.” (Fernyhough & Fradley, 2005: p. 1)

In addition to disagreeing on the functional significance of private speech, Vygotsky and Piaget also offered opposing views on the developmental course of private speech and the environmental circumstances in which it occurs most often (Berk & Garvin, 1984).

Functions of Private Speech

Through private speech, children collaborate with themselves in the same way a more knowledgeable other (e.g., adults) collaborates with them to achieve a given function.

Vygotsky sees “private speech” as a means for children to plan activities and strategies, aiding their development. Private speech is the use of language for self-regulation of behavior.

Private speech is not just aimless chatter; it serves a vital self-regulatory function. As children develop, they need to transition from relying on external guidance from adults to directing their own actions and thoughts.

Private speech emerges as a way for children to guide their own behavior, especially during challenging tasks. They are essentially verbalizing the thought process that will eventually become internalized as inner speech.

Berk (1986) provided empirical support for the notion of private speech. She found that most private speech exhibited by children serves to describe or guide the child’s actions.

Therefore, language accelerates thinking and understanding ( Jerome Bruner also views language this way). Vygotsky believed that children who engage in large amounts of private speech are more socially competent than children who do not use it extensively.

Vygotsky (1987) notes that private speech does not merely accompany a child’s activity but acts as a tool the developing child uses to facilitate cognitive processes, such as overcoming task obstacles, and enhancing imagination, thinking, and conscious awareness.

Children use private speech most often during intermediate difficulty tasks because they attempt to self-regulate by verbally planning and organizing their thoughts (Winsler et al., 2007).

Imagine a child working on a complex puzzle. They might say things like, “Where does this piece go? No, it doesn’t fit there. Maybe I should try turning it around.”

This self-directed talk helps them to:

• Focus attention : By verbalizing the problem and possible solutions, children are more likely to stay on task.
• Plan and sequence actions : Talking through the steps helps them organize their approach.
• Monitor progress : They can use their words to evaluate their success and make adjustments.

The frequency and content of private speech correlate with behavior or performance. For example, private speech appears functionally related to cognitive performance: It appears at times of difficulty with a task.

For example, tasks related to executive function (Fernyhough & Fradley, 2005), problem-solving tasks (Behrend et al., 1992), and schoolwork in both language (Berk & Landau, 1993), and mathematics (Ostad & Sorensen, 2007).

There is also evidence (Behrend et al., 1992) that those children who displayed the characteristic whispering and lip movements associated with private speech when faced with a difficult task were generally more attentive and successful than their ‘quieter’ classmates.

Developmental Trajectory

Berk also discovered that children engaged in private speech more often when working alone on challenging tasks and when their teacher was not immediately available to help them.

Furthermore, Berk also found that private speech develops similarly in all children regardless of cultural background.

Vygotsky (1987) proposed that private speech is a product of an individual’s social environment. This hypothesis is supported by the fact that there exist high positive correlations between rates of social interaction and private speech in children.

Children raised in cognitively and linguistically stimulating environments (situations more frequently observed in higher socioeconomic status families) start using and internalizing private speech faster than children from less privileged backgrounds.

Indeed, children raised in environments characterized by low verbal and social exchanges exhibit delays in private speech development.

As children become more adept at a task, their private speech typically becomes quieter and less grammatically complete.

This process of internalization involves “syntactic and semantic abbreviation,” meaning children start using a sort of mental shorthand, reflecting their increasing mastery of the task and the underlying cognitive processes. Eventually, this abbreviated private speech transforms into silent inner speech.

Children’s use of private speech diminishes as they grow older and follows a curvilinear trend. This is due to changes in ontogenetic development whereby children can internalize language (through inner speech) to self-regulate their behavior (Vygotsky, 1987).

For example, research has shown that children’s private speech usually peaks at 3–4 years of age, decreases at 6–7, and gradually fades out to be mostly internalized by age 10 (Diaz, 1992).

Vygotsky proposed that private speech diminishes and disappears with age not because it becomes socialized, as Piaget suggested, but because it goes underground to constitute inner speech or verbal thought” (Frauenglass & Diaz, 1985).

Inner Speech

Inner speech develops from private speech. As Vygotsky (1987) proposed, private speech “goes underground” to become inner speech.

Inner speech is a silent, internal language of thought that we use to reason, plan, and regulate our behavior. Unlike private speech, which is outwardly audible self-talk, inner speech is a completely internal process.

Vygotsky viewed language as a “tool” that mediates between our thoughts and actions. In the context of inner speech, language provides the very structure and form for our internal dialogue. It’s how we represent ideas, construct arguments, and engage in mental problem-solving.

Our capacity for silent thought (inner speech) is not an innate ability but rather a developmental achievement that emerges from our social world.

• Our earliest experiences with language and dialogue shape the very structure of our internal thought processes.
• Language acts as a tool, a system of representation, that enables us to think and reason internally.
• We carry the patterns and structures of social dialogue into our private mental landscapes.

The quality and development of inner speech can vary significantly across individuals. Factors such as social experiences, cultural background, and even the presence of developmental differences can influence the way inner speech manifests and its role in cognitive functioning.

Characteristics 

• Social dialogue : Inner speech is not merely a solitary monologue but retains the dialogic structure of social interaction. This means that when we engage in inner speech, we are essentially conversing with ourselves, mentally rehearsing different viewpoints, considering alternatives, and working through problems using language as the primary tool.
• Abbreviated and telegraphic: Inner speech is typically highly condensed, lacking the full grammatical structure of spoken language. This is because, in our own minds, we don’t need to state every detail explicitly. We can rely on shared context and understanding implicit in our internal dialogue.
• Simultaneity of perspectives:   A key characteristic of mature inner speech is the ability to hold multiple perspectives simultaneously. Rather than a linear, back-and-forth exchange, inner speech can encompass a complex interplay of ideas, allowing for more nuanced and flexible thinking.
• Planning and problem solving: Inner speech is essential for planning future actions, considering potential consequences, and developing strategies for navigating challenges.
• Self-regulation and control: Inner speech facilitates self-regulation, as it allows us to inhibit impulsive behaviors, stay focused on goals, and manage our emotions and motivations.
• Social understanding: There is a link between inner speech and our capacity to understand others’ minds. Engaging in internal dialogue, mentally representing different perspectives, might lay the groundwork for making sense of others’ thoughts, feelings, and intentions.

Educational Implications

Vygotsky’s approach to child development is a form of social constructivism , based on the idea that cognitive functions are the products of social interactions.

Social constructivism posits that knowledge is constructed and learning occurs through social interactions within a cultural and historical context.

Vygotsky emphasized the collaborative nature of learning by constructing knowledge through social negotiation. He rejected the assumption made by Piaget that it was possible to separate learning from its social context.

Vygotsky believed everything is learned on two levels. First, through interaction with others, then integrated into the individual’s mental structure.

Every function in the child’s cultural development appears twice: first, on the social level, and later, on the individual level; first, between people (interpsychological) and then inside the child (intrapsychological). This applies equally to voluntary attention, to logical memory, and to the formation of concepts. All the higher functions originate as actual relationships between individuals. (Vygotsky, 1978, p.57)

Teaching styles grounded in constructivism represent a deliberate shift from traditional, didactic, memory-oriented transmission models (Cannella & Reiff, 1994) to a more student-centered approach.

Traditionally, schools have failed to foster environments where students actively participate in their own and their peers’ education. Vygotsky’s theory, however, calls for both the teacher and students to assume non-traditional roles as they engage in collaborative learning.

Rather than having a teacher impose their understanding onto students for future recitation, the teacher should co-create meaning with students in a manner that allows learners to take ownership (Hausfather, 1996).

For instance, a student and teacher might start a task with varying levels of expertise and understanding. As they adapt to each other’s perspective, the teacher must articulate their insights in a way that the student can comprehend, leading the student to a fuller understanding of the task or concept.

The student can then internalize the task’s operational aspect (“how to do it”) into their inner speech or private dialogue. Vygotsky referred to this reciprocal understanding and adjustment process as intersubjectivity.

Because Vygotsky asserts that cognitive change occurs within the zone of proximal development, instruction would be designed to reach a developmental level just above the student’s current developmental level.

Vygotsky proclaims, “learning which is oriented toward developmental levels that have already been reached is ineffective from the viewpoint of the child’s overall development. It does not aim for a new stage of the developmental process but rather lags behind this process” (Vygotsky, 1978).

Appropriation is necessary for cognitive development within the zone of proximal development. Individuals participating in peer collaboration or guided teacher instruction must share the same focus to access the zone of proximal development.

“Joint attention and shared problem solving is needed to create a process of cognitive, social, and emotional interchange” (Hausfather,1996).

Furthermore, it is essential that the partners be on different developmental levels and the higher-level partner be aware of the lower’s level. If this does not occur or one partner dominates, the interaction is less successful (Driscoll, 1994; Hausfather, 1996).

Vygotsky’s theories also feed into the current interest in collaborative learning, suggesting that group members should have different levels of ability so more advanced peers can help less advanced members operate within their ZPD.

Scaffolding and reciprocal teaching are effective strategies to access the zone of proximal development.

Reciprocal Teaching

A contemporary educational application of Vygotsky’s theory is “reciprocal teaching,” used to improve students” ability to learn from text.

In this method, teachers and students collaborate in learning and practicing four key skills: summarizing, questioning, clarifying, and predicting. The teacher’s role in the process is reduced over time.

Reciprocal teaching allows for the creation of a dialogue between students and teachers. This two-way communication becomes an instructional strategy by encouraging students to go beyond answering questions and engage in the discourse (Driscoll, 1994; Hausfather, 1996).

A study conducted by Brown and Palincsar (1989) demonstrated the Vygotskian approach with reciprocal teaching methods in their successful program to teach reading strategies.

The teacher and students alternated turns leading small group discussions on a reading. After modeling four reading strategies, students began to assume the teaching role.

The results showed significant gains over other instructional strategies (Driscoll, 1994; Hausfather,1996).

Cognitively guided instruction is another strategy to implement Vygotsky’s theory. This strategy involves the teacher and students exploring math problems and then sharing their problem-solving strategies in an open dialogue (Hausfather,1996).

Based on Vygotsky’s theory, the physical classroom would provide clustered desks or tables and workspace for peer instruction, collaboration, and small-group instruction. Learning becomes a reciprocal experience for the students and teacher.

Like the environment, the instructional design of the material to be learned would be structured to promote and encourage student interaction and collaboration. Thus the classroom becomes a community of learning.

Also, Vygotsky’s theory of cognitive development on learners is relevant to instructional concepts such as “scaffolding” and “apprenticeship,” in which a teacher or more advanced peer helps to structure or arrange a task so that a novice can work on it successfully.

A teacher’s role is to identify each individual’s current level of development and provide them with opportunities to cross their ZPD.

A crucial element in this process is the use of what later became known as scaffolding; the way in which the teacher provides students with frameworks and experiences which encourage them to extend their existing schemata and incorporate new skills, competencies, and understandings.

Scaffolding describes the conditions that support the child’s learning, to move from what they already know to new knowledge and abilities.

Scaffolding requires the teacher to allow students to extend their current skills and knowledge.

During scaffolding, the support offered by an adult (or more knowledgeable other) gradually decreases as the child becomes more skilled in the task.

As the adult withdraws their help, the child assumes more of the strategic planning and eventually gains competence to master similar problems without a teacher’s aid or a more knowledgeable peer.

It is important to note that this is more than simply instruction; learning experiences must be presented in such a way as to actively challenge existing mental structures and provide frameworks for learning.

Five ways in which an adult can “scaffold” a child’s learning:

• Engaging the child’s interest
• Maintaining the child’s interest in the task e.g., avoiding distraction and providing clear instructions on how to start the task.
• Keeping the child’s frustration under control e.g., by supportive interactions, adapting instructions according to where the child is struggling.
• Emphasizing the important features of the task
• Demonstrating the task: showing the child how to do the task in simple, clear steps.

As the child progresses through the ZPD, the necessary scaffolding level declines from 5 to 1.

The teacher must engage students’ interests, simplify tasks to be manageable, and motivate students to pursue the instructional goal.

In addition, the teacher must look for discrepancies between students” efforts and the solution, control for frustration and risk, and model an idealized version of the act (Hausfather, 1996).

Challenges to Traditional Teaching Methods

Vygotsky’s social development theory challenges traditional teaching methods. Historically, schools have been organized around recitation teaching.

The teacher disseminates knowledge to be memorized by the students, who in turn recite the information to the teacher (Hausfather,1996).

However, the studies described above offer empirical evidence that learning based on the social development theory facilitates cognitive development over other instructional strategies.

The structure of our schools does not reflect the rapid changes our society is experiencing. The introduction and integration of computer technology in society has tremendously increased the opportunities for social interaction.

Therefore, the social context for learning is transforming as well. Whereas collaboration and peer instruction were once only possible in shared physical space, learning relationships can now be formed from distances through cyberspace.

Computer technology is a cultural tool that students can use to meditate and internalize their learning. Recent research suggests changing the learning contexts with technology is a powerful learning activity (Crawford, 1996).

If schools continue to resist structural change, students will be ill-prepared for the world they will live.

Critical Evaluation

Vygotsky’s work has not received the same level of intense scrutiny that Piaget’s has, partly due to the time-consuming process of translating Vygotsky’s work from Russian.

Also, Vygotsky’s sociocultural perspective does not provide as many specific hypotheses to test as Piaget’s theory, making refutation difficult.

Risk of Overemphasizing Environmental Influence

Vygotsky overemphasized socio-cultural factors at the expense of biological influences on cognitive development.

Vygotsky prioritized the role of cultural tools and social interaction in shaping mental processes, but paid insufficient attention to innate cognitive abilities and developmental processes that unfold more independently of social influence.

This imbalance in focus potentially led Vygotsky to underestimate the impact of elementary mental functions (arising from the natural line) on the development of higher mental functions (shaped by cultural tools). 

Vygotsky’s theory cannot explain why cross-cultural studies show that the stages of development (except the formal operational stage ) occur in the same order in all cultures suggesting that cognitive development is a product of a biological process of maturation.

Lack of Attention to Emotional Development

The theory is criticized for focusing primarily on cognitive development while neglecting the emotional and social-emotional aspects of development.

Modern developmental psychology recognizes that cognitive and emotional development are deeply intertwined. Critics argue that Vygotsky’s theory doesn’t adequately address how emotions influence cognitive processes and vice versa.

• While Vygotsky emphasized the social nature of learning, he didn’t extensively explore how children develop emotional intelligence or learn to regulate their emotions through social interactions.
• The concept of ZPD focuses on cognitive tasks, but critics argue it should also consider emotional challenges and how supportive relationships help children develop emotional competencies.
• The process of internalization in Vygotsky’s theory focuses on cognitive processes, but critics argue it should also consider how children internalize emotional coping strategies and understanding.

Vague Explanation of Internalization

People take in (internalize) dialogues and guidance they’ve received from others who are more knowledgeable. This internalized information is then used to guide their own actions and thinking.

While Vygotsky considered internalization a cornerstone of his theory, he did not fully articulate the specific mechanisms by which this process occurs. 

This concept is important because it describes how social interactions and cultural contexts contribute to individual cognitive development.

The idea is that higher mental functions first exist in the social realm (between people) before becoming internalized and part of an individual’s cognitive processes.

Eurocentric Bias

Vygotsky saw cultural development like a ladder, with European culture at the top. This view implies some cultures are “better” than others.

Vygotsky’s tendency to view cultural development as a linear hierarchy (often positioning European culture at the apex) can lead to:

• An oversimplification of cultural differences
• An underappreciation of the unique strengths and values of diverse cultural perspectives

A more nuanced approach, recognizing the heterogeneity of cultural tools and the situated nature of cognitive development, would better reflect the complexity of cultural influences on human thought and behavior.

Collaborative ZPD

Collaborative ZPD challenges traditional interpretations of ZPD that focus on the asymmetry between a more knowledgeable individual and a less knowledgeable learner.

Instead, a collaborative ZPD emphasizes the symmetrical nature of learning within peer interactions, where knowledge is co-constructed through mutual contributions and challenges, even among individuals with comparable expertise.

Collaborative ZPD represents a shift from viewing learning as an individual endeavor to recognizing it as a social practice (Tudge, 1992).

The most significant aspect of the ZPD is not the individual benefits gained by participants but the emergence of “a new form of collective consciousness,” highlighting how the interaction creates something new that transcends the contributions of any single individual.

Teachers need to go beyond simply placing students in groups and instead create conditions that foster genuine collaboration, characterized by:

• Transactive discussion, where students clarify, elaborate, justify, and critique their own and each other’s reasoning.
• Opportunities for students to challenge each other’s thinking, prompting metacognitive awareness and deeper engagement with the content.

Vygotsky vs. Piaget

Unlike Piaget’s notion that children’s cognitive development must necessarily precede their learning, Vygotsky argued, “learning is a necessary and universal aspect of the process of developing culturally organized, specifically human psychological function” (1978, p. 90). 

In other words, social learning precedes (i.e., come before) development.

Vygotsky’s theory differs from that of Piaget in several important ways:

Vygotsky places more emphasis on how culture affects cognitive development.

Unlike Piaget, who emphasized universal cognitive change (i.e., all children would go through the same sequence of cognitive development regardless of their cultural experiences), Vygotsky leads us to expect variable development depending on cultural diversity. 

This contradicts Piaget’s view of universal stages of development (Vygotsky does not refer to stages like Piaget does).

Hence, Vygotsky assumes cognitive development varies across cultures, whereas Piaget states cognitive development is mostly universal across cultures.

Vygotsky places considerably more emphasis on social factors contributing to cognitive development.

• Vygotsky states the importance of cultural and social context for learning. Cognitive development stems from social interactions from guided learning within the zone of proximal development as children and their partners co-construct knowledge. In contrast, Piaget maintains that cognitive development stems largely from independent explorations in which children construct knowledge.

The importance of scaffolding and language may differ for all cultures. Rogoff (1990) emphasizes the importance of observation and practice in pre-industrial societies (e.g., learning to use a canoe among Micronesian Islanders).

Vygotsky places more (and different) emphasis on the role of language in cognitive development.

According to Piaget , language depends on thought for its development (i.e., thought comes before language). For Vygotsky, thought and language are initially separate systems from the beginning of life, merging at around three years of age, producing verbal thought (inner speech).

In Piaget’s theory, egocentric (or private) speech gradually disappears as children develop truly social speech, in which they monitor and adapt what they say to others.

Vygotsky disagreed with this view, arguing that as language helps children to think about and control their behavior, it is an important foundation for complex cognitive skills.

As children age, this self-directed speech becomes silent (or private) speech, referring to the inner dialogues we have with ourselves as we plan and carry out activities.

For Vygotsky, cognitive development results from an internalization of language.

According to Vygotsky, adults are an important source of cognitive development.

Adults transmit their culture’s tools of intellectual adaptation that children internalize.

In contrast, Piaget emphasizes the importance of peers, as peer interaction promotes social perspective-taking.

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Further Reading

What is vygotsky’s theory.

Vygotsky believed that cognitive development was founded on social interaction. According to Vygotsky, much of what children acquire in their understanding of the world is the product of collaboration.

How is Vygotsky’s theory applied in teaching and learning?

Vygotsky’s theory has profound implications for classroom learning. Teachers guide, support, and encourage children, yet also help them to develop problem-solving strategies that can be generalized to other situations.

Children learn best not when they are isolated, but when they interact with others, particularly more knowledgeable others who can provide the guidance and encouragement to master new skills.

What was Vygotsky’s best know concept?

Lev Vygotsky was a seminal Russian psychologist best known for his sociocultural theory. He constructed the idea of a zone of proximal development ,  which are those tasks which are too difficult for a child to solve alone but s/he can accomplish with the help of adults or more skilled peers.

Vygotsky has developed a sociocultural approach to cognitive development. He developed his theories at around the same time as  Jean Piaget  was starting to develop his ideas (1920’s and 30″s), but he died at the age of 38, and so his theories are incomplete – although some of his writings are still being translated from Russian.

Like Piaget, Vygotsky could be described as a  constructivist , in that he was interested in knowledge acquisition as a cumulative event – with new experiences and understandings incorporated into existing cognitive frameworks.

However, while Piaget’s theory is structural (arguing that physiological stages govern development), Vygotsky denies the existence of any guiding framework independent of culture and context.

No single principle (such as Piaget’s equilibration) can account for development. Individual development cannot be understood without reference to the social and cultural context within which it is embedded. Higher mental processes in the individual have their origin in social processes.

What is Vygotsky’s Social Development Theory?

Vygotsky’s Social Development Theory is often referred to as the Sociocultural Theory.

Vygotsky’s Social Development Theory posits that social interaction is fundamental to cognitive development. Vygotsky emphasized the influence of cultural and social contexts on learning, claiming that knowledge is constructed through social collaboration.

His most known concept, the Zone of Proximal Development, refers to the difference between what a learner can do independently and what they can achieve with guidance.

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Supporting preschoolers’ cognitive development: Short‐ and mid‐term effects of fluid reasoning, visuospatial, and motor training

Valentina gizzonio.

1 Istituto di Neuroscienze, Consiglio Nazionale delle Ricerche (CNR), Parma Italy

Maria Chiara Bazzini

Cosima marsella, pamela papangelo, giacomo rizzolatti, maddalena fabbri‐destro, associated data.

Cognitive abilities are essential to children's overall growth; thus, the implementation of early and effective training interventions is a major challenge for developmental psychologists and teachers. This study explores whether an intervention simultaneously operating on fluid reasoning (FR), visuospatial, narrative, and motor abilities could boost these competencies in a group of Italian preschoolers ( N  = 108, 54 males 54 females, Age mean  = 4.04). FR and visuospatial abilities showed training‐related increases at the end of the training and 1‐year follow‐up (moderate effect size). Interestingly, positive correlations with working memory and mathematical abilities were found. Beyond their scientific relevance, the short‐ and long‐term effects provide fundamental indications for designing and implementing educational programs dedicated to preschoolers.

Abbreviations

The preschool period (3–6 years) is a time of rapid growth along which many changes happen in children's development. During this period, children learn new skills belonging to fundamental domains like social and emotional abilities and cognitive development (Haddad et al., 2019 ). Cognitive development refers to the process of growth and change in intellectual/mental abilities such as thinking, reasoning, and understanding, including the acquisition and consolidation of knowledge. Children this age begin to learn questioning, spatial relationships, problem‐solving, imitation, number sense, and symbolic play. Such a constellation of functions is vital to the child's overall growth and development (Rueda et al., 2005 ; Thorell et al., 2009 ; Wass et al., 2011 ). Thus, early and effective training interventions—possibly embeddable in everyday life—are among the major challenges for developmental psychologists and teachers (see Goswami, 2015 ; Kuhn & Siegler, 1998 ).

A broad range of cognitive competencies progresses during early childhood. Among them, we focused our attention on fluid reasoning (FR), visuospatial, linguistic, and motor abilities, intending to propose to preschool children an intervention simultaneously touching upon all these competencies.

Problem solving is the cognitive process for achieving a goal when a solution method is not obvious to the problem solver (Lovett, 2002 ; Mayer, 1992 ). It is part of the more general domain called fluid intelligence or FR. According to the Cattell–Horn–Carroll theory, FR is defined as the deliberate but flexible control of attention to solve novel on‐the‐spot problems that cannot be performed by relying exclusively on habits, previously learned schemas, and scripts (see Schneider & McGrew, 2018 ). It is an essential component of cognitive development (Goswami, 1992 ) since this capacity serves as a scaffold for children, helping them acquire other abilities (Blair, 2006 ; Cattell, 1971 , 1987 ; Ferrer et al., 2009 ).

FR predicts performance on a wide range of cognitive activities, including performance in school, university, and cognitively demanding occupations (Gottfredson, 1997 ), and some studies have demonstrated that low FR in children is a predictor of academic difficulties (Lynn et al., 2007 ; Nisbett, 2009 ).

Whether FR can be improved with training has been investigated with different strategies across the lifespan (Plemons et al., 1978 ). While studies on healthy adults yielded disappointing results (e.g., Detterman & Sternberg, 1982 ), FR has been successfully trained in children (Christoforides et al., 2016 ; Hamers et al., 1998 ; Hernstein et al., 1986 ; Klauer et al., 2002 ; Niklas et al., 2016 ), promoting early math skill development in kindergarten and elementary school age. In particular, Bergman Nutley et al. ( 2011 ) administered to 4‐year‐old children computerized training of either non‐verbal reasoning, working memory, a combination of both, or a placebo version of the combined training. Only the non‐verbal reasoning training significantly impacts FR, while smaller gains on problem‐solving tests were seen in the other groups. Similarly, Mackey et al. ( 2011 ) compared in children (aged 7–9) the effects of two computerized training programs focused on FR and processing speed (PS). Both training programs led to significant improvements in the cognitive domain targeted explicitly by the training, with no cross‐talk between FR and PS. Overall, evidence was provided about the possibility of improving FR (see for a review Buschkuehl & Jaeggi, 2010 ) in children (Jaeggi et al., 2008 , 2011 ; Sternberg, 2008 ), adults (Ball et al., 2002 ), and atypically developing populations (Klingberg et al., 2002 , 2005 ). However, no indication has been provided to date how long these training effects last (Jaeggi et al., 2008 ; Spitz, 1992 ). Moreover, computerized training is performed individually by children (see Mackey et al., 2011 ), lacking the motivational and imitative drives typical of the social environment in which children learn together with their peers.

Strictly related to FR, spatial skills are another critical component of cognitive development in children. They are considered an umbrella term for a constellation of inter‐related abilities as, for example, the capacity to mentally manipulate the object information or visualize how objects fit together (see Uttal et al., 2013 ). Better performers in spatial tasks typically have higher mathematical abilities, as proved by behavioral and neuropsychological measures (Guay & McDaniel, 1977 ; Mix & Cheng, 2012 ; Xie et al., 2020 ).

The effectiveness of training interventions on spatial skills has been previously shown (Kim et al., 2018 ; Verdine et al., 2014 ). The time spent playing with assembly toys has a pivotal role (Jirout & Newcombe, 2015 ). Interestingly, contextual elements emerged as relevant for the training outcome beyond the spatial content of these activities. Casey et al. ( 2008 ) combined a block‐building intervention with storytelling procedures, demonstrating that storytelling enhances spatial learning. Grounding spatial tasks in a storytelling context could produce greater retention and recall of the information (Bower & Clark, 1969 ) and engage children's motivation in solving the spatial task (Casey et al., 2008 ).

When exposed to narration, children experience a sort of continuum ranging from the discursive exposition in storytelling to their enactment in a play‐like situation (Nicolopoulou & Richner, 2007 ; Nicolopoulou et al., 2014 ). A series of research demonstrated that children's acquisition of oral language skills in their preschool years, including narrative ones, is a foundation for academic abilities such as reading comprehension, writing reports, and formulating oral presentations (Griffin et al., 2004 ; Kendeou et al., 2009 ; Lynch et al., 2008 ; Nicolopoulou et al., 2015 ; Reese et al., 2010 ). Thus, training narrative abilities at an early stage would help individuals to exploit at best later their language skills.

Even if out of the traditional cognitive domains, decades of psychological theory and research have established that motor abilities are strictly intertwined with cognitive development in infancy and early childhood (e.g., Adolph, 2008 ; Davis et al., 2011 ; Piaget, 1952 ). Since the earliest developmental stages, the unfolding of cognitive abilities appears influenced by the onset of corresponding motor skills (e.g., exploration capacity vs. locomotion, Lehnung et al., 2003 ). This link, however, is not limited to the early timing, as the two domains follow a comparable and progressive timetable (Bushnell & Boudreau, 1993 ) also during later development. Positive relations between motor and cognitive domains have also been supported by neuropsychological and neuroimaging studies (Diamond, 2000 ; Wassenberg et al., 2005 ).

The pathological counterpart of this interplay is represented by the cognitive impairments following a delay or deviance in targeting motor developmental milestones. For example, idiopathic toe walking is considered a precursor of developmental language and learning problems (Sala et al., 1999 ). Impaired motor function is a precursor of language acquisition problems and later attention skills (Amiel‐Tison et al., 1996 ; Hamilton, 2002 ).

While attempts to train the abovementioned abilities have been carried out mainly in isolation, that is, addressing one specific domain at a time, we sought to design an intervention touching upon all these domains. We enrolled 157 preschoolers (3–5 years old) and administered them a training procedure stimulating FR, visuospatial and motor skills, and narrative abilities. Children were subdivided into three groups, differing for the activities they were exposed to during training. A neuropsychological battery was administered before and after the training and at 1‐year follow‐up to evaluate short‐term impacts and maintenance over time. While the first analysis can be considered confirmatory, as an immediate impact of the training is lagerly expected on some domains, the latter can be regarded as more exploratory, because it is far from granted that the training effects can resist after 1 year. Results will be discussed in light of the potential of preschool daily practice to potentiate emerging skills and prompt the acquisition of new ones fundamental for children's future learning and discoveries.

Participants

In 2016, an initial sample of 157 preschoolers was enrolled in the study across five different kindergartens in Parma (Italy). Kindergartens in Italy are a preschool service for children from 3 to 5 years old, preceding the access to the primary school that happens at 6 years old. Informed written consent was obtained from the parents and oral consent from the children. The Local Ethical Committee approved this study (prot. n. 45017, 14‐12‐2015), which was conducted according to the Helsinki Declaration.

Study design

The study was articulated in five different moments, including (1) an initial screening conducted on 157 children; (2) a neuropsychological evaluation administered before the intervention (T0); (3) the administration of a training (32 sessions), namely intervention; (4) a neuropsychological evaluation administered after the intervention, about 1 year after T0 (T1); and finally, (5) a follow‐up neuropsychological evaluation 1 year after T1 (T2). At T2, we administered additional tests to investigate the verbal and visuospatial working memory and the basic mathematical skills. The whole timeline lasted from 2016 to 2019.

Such experimental design aimed to obtain a global picture of children's skills before the treatment, after it, and 1 year later to identify the impact of the intervention on different domains, its maintenance over time, and the possible generalization to other domains not explicitly trained.

All children were admitted to a screening evaluating cognitive and linguistic abilities to exclude individuals with intellectual disabilities or language difficulties, potentially compromising the reliability of the study results.

The intelligence quotient (IQ) was evaluated by the Leiter International Performance Scale‐Revised (Leiter‐R; Roid & Miller, 2002 ). The linguistic domain was investigated administering three subtests of the NEPSY‐II (Korkman et al., 2011 ): comprehension of instruction (CI), phonological processing (PH), and speeded naming (SN).

Following the screening assessment and teachers’ reports, 13 children were not included in the training. Three had started a clinical evaluation at the local Neuropsychiatry Service, two were bilingual with difficulties in Italian language comprehension and production, and one was certified for visual and auditory difficulties. The remaining seven children could not adhere to the screening procedure and completed only partially the required tests preventing us from their inclusion in the experimental sample. A minimum threshold of 70 was required for Leiter‐R, and a score greater than five was needed for any of the linguistic subtests (CI, PH, SN). However, none of the children had scores below these thresholds. At the end of the screening, the sample to‐be‐included in the study was 144 children (78 girls; 66 boys) with ages from 3 to 5 years ( M  = 4 year1 month, SD  = 6 month).

Group assignment

After the screening, participants were subdivided into three groups according to the type of toys used during the training. Children playing with modular toys were required to assemble different pieces and were included in the Assembling group ( A ); children receiving plush toys were assigned to the Plush group ( P ); remaining children composed the Control group ( Ctrl ). While the first two groups would have been later administered with specific training, children of the control group continued curricular programs without attending any extra activity. The inclusion of a training‐free group let us control for the spontaneous development of cognitive abilities over time in a sample of participants attending the same schools and curricular activities.

Since the intervention was distributed across five different schools, their heterogeneity (e.g., districts, teachers, class size) could introduce several potentially confounding factors in our study. To account for most of them, we decided to balance the group numerosity within each school. Starting from this constraint, we first split the group according to age: children attending the first year of kindergarten and those attending the second year. Within each of these groups, we sorted children according to their IQ and then subdivided them into triplets. For each triplet (child 1, child 2, child 3), a computer‐generated sequence randomly assigned the three children to groups (e.g., PCA implies child 1 to P, child 2 to Ctrl, child 3 to A group).

This way, we warranted that groups were balanced in terms of IQ, and at the same time, they equally included the 2 years of kindergarten attendance, thus likely reflecting a further balance in terms of age. Since this procedure was replicated for each school, the overall sample benefited from the same balancing properties.

Intervention

The intervention was conducted during the regular kindergarten hours. As school numerosity was quite different (range 18–51), we further subdivided the experimental groups (Assembling and Plush) into smaller groups of 6–9 children to balance among schools the potential effect of team working. One of the three developmental psychologists (MCB, PP, CM) conducting the intervention was randomly assigned to each group.

The intervention sessions (approximately 50 min each) took place in a dedicated room within the school twice a week. The 32 sessions composing the training were distributed over about 5 months. Children assigned to the control group, on the contrary, continued curricular programs without attending any extra activity.

Each experimental session was characterized by four moments: toy delivery, the introduction of the story by the experimenter, turn‐based interplay, quizzing children with questions whose answer requires the solution of logical tasks, and retelling.

(a) Structure of the stories used during the training sessions. Each story contained open questions and logical tasks to stimulate the narrative domain and the emergence of problem‐solving capabilities. (b) Toys utilized during the training. Children of the Plush group received plush toys, while children of the Assembling group received a modular toy to be built following visual instructions. The Plush group's toy represented the same characters used by the Assembling group but in the "soft and big" version. (c) Scenery: a 3D set design was created for each story to provide a concrete context to the narration in which every child could act the story through his/her character

• 2) Stories: A set of 32 stories was used during the training. These were created by our team of psychologists maintaining the structural regularity of the narrative text (Levorato, 1988 ): introduction of the context and characters, an initial event that triggers the actions of the characters, several attempts to solve the problem, the consequences of such attempts, and finally a conclusion (see Figure ​ Figure1a). 1a ). The characters of each story corresponded to the toys delivered to children to make them actively participate in the story. An exemplar story used during the training can be found in Supporting Information . Scenery: A home‐made scenery was created for each story to provide children with a concrete space (e.g., a laboratory, the sea, or a forest) in which each child, through his character, could live and act the story Figure 1c shows an example of a 3D set used during the sessions.
• 3) Quizzing and interplay: Every story contained questions and logical tasks to stimulate the narrative domain and problem‐solving capabilities (see Figure ​ Figure1a). 1a ). In particular, four types of open questions were used: semantic (e.g., what is a scientist?), hypothetical (e.g., what will it happen then?), resolution of unexpected events (e.g., how can they cross the river?), and attribution of state questions (e.g., what does he/she think? what emotion does he/she feel?). Children were instructed to answer individually without reference to previous answers by other peers, thus promoting original responses. The experimenter repeated each answer enriching it with additional elements so to stimulate narrative competencies. While the open questions were answered individually, children solved the logical tasks collectively. These were subdivided into repeated patterns, seriation, and time‐sequence ordering tasks. Repeated pattern tasks required the child to understand a logical sequence and complete it considering the initially provided model. The seriation tasks required the child to compare elements (e.g., size, quantity, color) and identify the relations between them, recognizing the correct order. Finally, the time‐sequence ordering task required the child to reconstruct the temporal sequence respecting the logical and sequential order of events.
• 4) Retelling: Finally, children were invited to retell the story. In this schema, the toy becomes the physical bridge that lets children play the story. Indeed, they become part of the story via their characters, interact with other mates and characters, and succeed or fail collectively. This cooperative, active, and interactive scenario rendered the training more similar to a play context than a traditional trainer‐trainee relationship.

Neuropsychological evaluation

We administered a neuropsychological battery at three time‐points, that is, before the treatment (T0), after it (T1), and at 1‐year follow‐up (T2).

During the training session, children received questions about the story and implying logical tasks to boost their problem solving. The underlying function, that is, FR, was evaluated by Raven's Colored Progressive Matrices (Raven, 1984 ). The test measures relational reasoning and is considered the most specifically designed test to measure fluid intelligence (Cotton et al., 2005 ).

The visuospatial and motor abilities were evaluated by administering two subtests of the NEPSY–II (Korkman et al., 2011 ). The Block Construction subtest provides a measure of the ability to mentally organize visual information by analyzing part‐whole relation when the information was presented spatially. In the Imitating Hand Position subtest , the child imitates various hand positions demonstrated by the examiner, thus obtaining an index of his/her performance in terms of visuomotor transformation.

Finally, children's answers were repeated and enlarged by the experimenter so to promote their storytelling. The linguistic/narrative competence was evaluated using Information Scores ( IS ), Sentence Length ( SL ), and Subordinate Clauses ( SC ) scores from the Bus Story Test (I‐BST; Renfrew, 1997 ). The IS measures how many information units of the original story the child uses during the retelling. The SL indexes the morpho‐syntactic complexity of the retelling, and the SC score depends on the number of utterances containing a subordinate clause.

An additional battery was administered only at T2, comprising working memory and mathematical abilities assessment. Visuospatial and verbal working memory abilities were evaluated by administering the Memory for Designs (MD) and Sentence Repetition (SR) subtests of NEPSY‐II (Korkman et al., 2011 ), respectively. Mathematical abilities were assessed using the TEDI‐MATH test (Van Nieuwenhoven et al., 2015 ). Table ​ Table1 1 summarizes the investigated competencies, the related tests and subtests, and the time‐points at which each test was administered.

Neuropsychological battery. Investigated competencies, tests, subtests, and the timing (T0, T1, T2) of administration are reported. Visuospatial and Verbal Working Memory (WM) and mathematical skills are tested only at T2

Drop‐out

The children initially enrolled in the study were required to be 3 or 4 years old at T0, as they were attending the first or the second year of kindergarten at that time. At T1, they were still attending the same school, and all of them were recruited for re‐testing (144 T0, 144 T1). However, between T1 and T2, 36 children dropped out, including those who moved to different institutes or towns and those whose parents did not sign the informed consent for the follow‐up procedures. These 36 participants were excluded from the final sample to guarantee a complete dataset comprising pre and post‐intervention and follow‐up observations for all participants. Of the remaining 108 children, 41 remained for the whole study duration in kindergarten, while 67 moved to primary school.

Data analysis and statistics

The final sample of children admitted to data analysis comprised those having complete evaluation across T0, T1, and T2 and was composed of 108 children. A factorial analysis was conducted on scores reported in Table ​ Table2, 2 , intended at verifying the homogeneity among groups at baseline in terms of age, initial cognitive, and linguistic levels. Gender balance was assessed as well via a chi‐squared test.

Means and standard deviations of the measures collected during the screening

Concerning the tests listed in Table ​ Table1, 1 , we admitted to the analysis the raw scores and not the ones normalized per age. This choice was driven by a limitation intrinsic to our experimental design. Indeed, most of the tests would require a normalization procedure based on the child's chronological age, with steps 365 days long. However, because 394 (±27) days interspersed on average between T0 and T1, the impact of age‐normalization would have been tremendously different across children, with some of them remaining in the same year of normalization, and others advancing of two (and not just one) years of normalization. We thus opted to consider raw values to overcome this paradox, being aware that raw values are supposed to increase over time due to the spontaneous development of children's abilities, even regardless of our intervention. However, we aimed at revealing that such an increase had been higher in the case of children belonging to the experimental groups.

For this reason, we did not consider in the analysis the absolute values recorded at T0, T1, and T2, but rather the relative increases observed at T1 and T2 against T0 (i.e., Delta 1: T1–T0, Delta 2: T2–T0). Delta 1 was intended to index the immediate effectiveness of the intervention for each child in each domain. At the same time, Delta 2 served to evaluate whether these increases were possibly maintained at the 1‐year follow‐up, selectively across groups. We did not account for T2–T1 because such a difference would be devoid of any effect directly linked to the training.

Statistical analysis was conducted with a one‐way factorial design, including a between‐subjects factor (group: Ctrl , A , P ). All variables underwent the Shapiro–Wilk's W ‐test for verifying the assumption of normality. Screening variables underwent a one‐way ANOVA or Kruskal–Wallis analysis to assess the homogeneity of groups in terms of baseline characteristics. For Delta scores, statistical parametric analyses were performed via ANCOVA with Group as between‐subject factor and screening scores (Age, IQ, CI, SN, PH) as covariates. Newman–Keuls correction for multiple comparisons was applied. In the case of non‐parametric tests, Kruskal–Wallis and Mann–Whitney post hoc were used accordingly. Eta‐squared ( η 2 ) was calculated as a measure of effect size.

Finally, correlations (Pearson) against working memory (visuospatial and verbal indices) and mathematical abilities were conducted at T2 for all the scores significantly modulated across groups and maintained over time. Even though a correlation between differential scores would have been more conclusive, the lack of WM or MATH scores at T0 impeded us from isolating the contribution of our training to the development of these abilities. However, proving their interdependency at a given time point would suggest the potential of our findings to transfer to other cognitive skills.

While group assignment was conducted on the initial sample of the 144 children, we had no chance at T0 to predict how many and which children would have later dropped out. It is then important to ensure that the final sample (i.e., the three groups of 36 children each) remained matched in terms of age, cognitive, and linguistic skills at T0 to consider differences appearing at T1 and T2. On the 108 sample, the assumption of normality was not met for most of the screening variables. A non‐parametric Kruskal–Wallis indicated no significant difference among groups for age, IQ, CI, SN, and PH (all p s > .07). These data (see Table ​ Table2) 2 ) indicated that the selected population had comparable cognitive and linguistic levels, and no confounding bias was introduced even after that 36 children dropped out from the study.

While we controlled for gender during the group assignment, the relevant drop‐out from T0 to T2 (36 children) compromised the initial gender balance across groups, but this was out of our control (see Table ​ Table3). 3 ). To test quantitatively the gender bias of our final sample, we performed a 3 × 2 chi‐square test ( χ 2 (2, N  = 108) = 4.22, p  = .12) resulting not significant at p  < .05.

Group characteristics. The age is presented in years:months

As explained in Methods, the analysis focused on the differential scores between T1, T2 relative to T0. For completeness, all raw scores at the three time‐points are reported in Table ​ Table4, 4 , whereas Table ​ Table5 5 reports the differential scores Delta 1 and Delta 2 for all the investigated outcomes.

Neuropsychological evaluations at three time points. RCPM: Raven's Colored Progressive Matrices (fluid reasoning); NEPSY‐II—VS: Block Construction (visuospatial abilities); NEPSY‐II—FM: Imitating Hand Positions (fine motor abilities); I‐BST (Bus Story Test)—IS: Information Scores; I‐BST—SL: Sentence Length; I‐BST—SC: Subordinate Clauses (linguistic/narrative competence)

Means and standard deviations of Delta 1 and Delta 2 scores. RCPM: Raven's Colored Progressive Matrices (fluid reasoning); NEPSY‐II—VS: Block Construction (visuospatial abilities); NEPSY‐II—FM: Imitating Hand Positions (fine motor abilities); I‐BST (Bus Story Test)—IS: Information Scores; I‐BST—SL: Sentence Length; I‐BST—SC: Subordinate Clauses (linguistic/narrative competence)

The results for FR indicated a significant effect at Delta 1, F (2, 99) = 4.31, p  = .02, η 2  = .075 and at Delta 2, F (2, 99) = 4.77, p  = .01, η 2  = .080 (Figure ​ (Figure2a). 2a ). Post hoc analysis (Newman–Keuls) revealed that the two experimental groups significantly differed at Delta 1 from the control group ( M  = Ctrl: 2.3, A: 4.6, P: 4.3, both comparisons p  < .001) suggesting a specific effect of the intervention. The same pattern was obtained at Delta 2 ( M  = Ctrl: 5.9, A: 9.1, P: 7.9, both comparisons p  < .001) showing that the effect of treatment was maintained over time.

Scores for control, assembling, and plush groups at Delta 1 (T1–T0) and Delta 2 (T2–T0) for fluid reasoning (a) and visuospatial abilities (b). Bars indicate the standard error, while asterisks indicate scores significantly different between groups at post hoc analysis ( p  < .05)

Concerning the visuospatial scores, a significance difference was found across groups at Delta 1, F (2, 99) = 3.32, p  = .04, η 2  = .055 with higher scores for the Assembling group relative to other two ( M  = Ctrl: 2.7, A: 4.0, P: 2.9, A vs. Ctrl, p  = .02; A vs. P, p  = .03), but no difference between Control and Plush groups (Ctrl vs. P, p  = .61), as revealed by post hoc analysis. A similar pattern was revealed also by Delta 2 scores, with a significant group effect F (2, 99) = 3.67, p  = .03, η 2  = .067 and the Assembling group maintaining a higher level of visuospatial abilities ( M  = Ctrl: 3.6, A: 5.0, P: 3.9, A vs. Ctrl, p  = .04; A vs. P, p  = .05) (see Figure ​ Figure2b 2b ).

Regarding the motor domain, a main effect of group appeared at Delta 1, F (2, 99) = 7.39, p  = .001, η 2  = .12, with post hoc reporting a specific effect for both experimental groups relative to controls ( M  = Ctrl: 3.4, A: 6.6, P: 5.6, both comparisons p  < .001). However, the increase in motor abilities for the experimental groups was not anymore significant when examining Delta 2 scores, F (2, 99) = 0.35, p  = .70, ( M  = Ctrl: 7.8, A: 8.6, P: 8.5).

Considering the linguistic/narrative domain, IS (Delta 1, F (2, 99) = 0.36, p  = .70; Delta 2, F (2, 99) = 0.22, p  = .81) and SL (Delta 1, F (2, 99) = 1.53, p  = .22; Delta 2, F (2, 99) = 0.66, p  = .52) showed no significant effect. The same happened for SC at both Delta 1 (Kruskal–Wallis: H (2, N  = 108) = 5.11, p  = .08) and Delta 2 (Kruskal–Wallis: H (2, N  = 108) = 2.57, p  = .28). Mean Delta scores are reported in Table ​ Table5. 5 . Overall, linguistic/narrative competences were poorly affected by our intervention.

In summary, we found that the intervention designed in the present study had a significant impact on FR and visuospatial abilities, whose scores remained selectively higher also at 1‐year follow‐up. In particular, both experimental groups showed a beneficial effect for FR relative to the control group. Only the Assembling group received specific training for visuospatial abilities and presented higher scores in this domain at both time points.

Following these results, we tested whether at T2 the trained competencies could be positively correlated with working memory (visuospatial—MD, and verbal—SR) and mathematical abilities (i.e., number processing and calculation) indices. Results, reported in Figure ​ Figure3, 3 , showed a significant and positive correlation between FR and MD ( r  = .57, p  < .001) as well as with SR ( r  = .41, p  < .001). Visuospatial abilities also positively correlated with MD, as well as with SR ( r  = .42, p  < .001; r  = .37, p  < .001, respectively). Of note, in the latter case, three participants appear as outliers, as visible in Figure ​ Figure3d 3d (bottom right part of the graph). While we did not remove these participants for the sake of completeness, it is worth indicating that their deletion increases the correlation coefficient from .37 to .49, thus offering an even stronger picture of this finding.

Upper part: Results of the correlation analyses between fluid reasoning and visuospatial working memory (a) scores ( r  = .57, p  < .001), and fluid reasoning and verbal working memory (b) scores ( r  = .41, p  < .001). Lower part: Results of the correlation analyses between visuospatial abilities and visuospatial working memory ( r  = .42, p  < .001), left side (c) and visuospatial abilities and verbal working memory ( r  = .36, p  < .001), right side (d). Each dot indicates a single participant. The solid black line indicates the linear fitting

Regarding the relation with the mathematical ability score, we split the sample into two groups according to age, as the TEDI‐MATH provides different tasks for preschool and school children. In preschool children, the correlation between FR and mathematical abilities indicated a positive correlation ( r  = .28, p  = .02), but only a trend emerged for the correlation with visuospatial abilities ( p  = .08). In school children the analyses revealed strong, positive and significant correlations between both FR and visuospatial abilities against mathematical ones ( r  = .71, p  < .001; r  = .40, p  = .007, respectively; Figure ​ Figure4 4 ).

Left side: Results of the correlation analyses in preschool subgroup between fluid reasoning (a) and Math (c) scores ( r  = .28, p  = .02), and between visuospatial abilities and Math scores ( r  = .23, p  = .07). Right side: Correlation analyses in school subgroup between both fluid reasoning (b) ( r  = .71, p  < .001) and visuospatial abilities (d) ( r  = .40, p  = .01) against mathematical abilities. Each dot indicates a single participant. The solid black line indicates the linear fitting

In this study, we designed an intervention for preschool children addressing simultaneously different cognitive and motor domains yet containing features easy to transfer into everyday kindergarten practice. As the proposed intervention was centered on problem solving, narrative competencies, and visuomotor abilities, we first investigated whether its administration could enhance these domains. The results showed that FR and motor abilities were enhanced in both experimental groups (i.e., regardless of the type of toy they interacted with), while only the interaction with modular toys determined an increase in visuospatial abilities. Finally, the linguistic/narrative domain did not take advantage of the training for any group.

The second aim was to determine whether training effects were stable over time. For this purpose, all children were evaluated after 2 years since the beginning of the study. Notably, all increases in FR (for both experimental groups) and visuospatial abilities (for the Assembling group only) showed a maintenance effect, with significant effects resisting despite 1 year of non‐training. In other words, our training impacted the present cognitive abilities and set better premises for future development. The moderate effect size at T2 further reinforces the value of our findings. Looking comparatively to the two types of training, the significant and long‐lasting modulation of visuospatial abilities indicates that assembling training addresses the larger set of cognitive skills. In the next paragraphs, we will discuss each domain separately.

Fluid reasoning is considered one of the most important factors in learning, critical for a wide variety of cognitive tasks (Gray & Thompson, 2004 ). However, whether FR can be trained is a matter of debate. While traditionally considered a trait with a strong hereditary component (Baltes et al., 1999 ; Gray & Thompson, 2004 ) and therefore rather immune against training, recent studies succeeded in training FR (see Klauer & Phye, 2008 ). Our study confirms that exposing children to problem‐solving tasks enhances FR skills for at least 12/24 months. This aspect assumes fundamental importance in the debate about how durable FR training is, as increases obtained through training programs have often proved to be fleeting (Spitz, 1992 ). The impact of our training on FR was durable, not vanishing shortly after the end of the training, potentially setting better premises for the development of other cognitive abilities and later professional and educational success (Deary et al., 2007 ; Neisser et al., 1996 ).

While a detailed comparison of our intervention relative to the procedures previously reported in the literature is virtually impossible, two peculiar aspects may have contributed to its success in modulating FR. The first is represented by the social context in which the training took place, contrary to computerized training programs to be performed individually (Bergman Nutley et al., 2011 ; Mackey et al., 2011 ). The social context may have driven imitative behaviors and boosted motivation to participate in the activities. The relational processes that occur when young children engage with others constitute a platform for advancing children's cognitive abilities. The second aspect is represented by the play‐like setting, highly distant from the laboratory‐ or class‐like environments, instantiated by toys and their enactment into the shared, narrated story.

Our training also enhanced fine‐motor abilities. A specific effect was expected only for the Assembling group, whose children spent the time in activities (e.g., building a toy) that required fine motor competencies. After the training, an improvement was found in both experimental groups, but this effect vanished at T2. The unspecificity and fleetingness of these findings might be linked to an insufficient time of exposition or inadequate sensitivity of the test used for the evaluation. Indeed, 32 play sessions might not suffice to make an increase in fine motor abilities emerge for the group exposed to modular toys. While the delivered amount of training seemed initially relevant, the young age of the experimental groups, together with the longer maturation time required by fine‐motor skills relative to the gross‐motor ones (see Gasser et al., 2010 ), may have blurred the expected outcome. A complementary explanation concerns the test adopted for the motor evaluation. The Imitating Hand Position subtest (NEPSY‐II) is designed to assess the ability to imitate static hand and finger configurations. Thus, it is probably more sensitive to postural imitation skills than abilities underlying fine and sequential movements. Despite this globally negative result, indexing fine motor skills in preschool children is fundamental given the relevance in driving later development. For this reason, future studies should consider using longer or more intensive training and the adoption of neuropsychological or neuro‐motor tests more sensitive to subtle increases of motor functioning (see Movement Assessment Battery for Children—Second Edition, Henderson et al., 2007 ).

A clear difference between experimental groups emerged after the training in the visuospatial domain. Indeed, to construct their toys, children of the Assembling group, but not children of the Plush group, had to follow visual instructions, commuting 2D visual images into 3D toys. This activity selectively involves the individual's capacity to manipulate and transform visual information to obtain a final goal. The specificity of the increase for the Assembling group supports the idea of the malleability and upgradability of visuospatial skills after specific training. Similar conclusions were reached by Casey et al. ( 2008 ) investigating the use of block‐building interventions to develop spatial‐reasoning skills in children of the same age as in this study.

Although the retelling represented one important element of our intervention, no significant impact was found in the linguistic/narrative domain. Indeed, I‐BST scores increased along observation times but with no modulation across groups (see Table ​ Table1; 1 ; Supporting Information ). This finding could be due to the low dosage of narrative training administered to children. In other words, 32 sessions in a year may not have been capable of super‐adding a meaningful enhancement to the physiological development of linguistic abilities, which are daily trained in educational and social environments.

In conclusion, our training during preschool years sustains the emergence of FR and visuospatial abilities and their maintenance over time. Using a correlative approach, we highlighted positive correlations of these scores against mathematical skills and working memory.

The link between spatial abilities and mathematics is well established (e.g., Dehaene et al., 1999 ), even if different hierarchies have been proposed. On one side, spatial reasoning could overlap and serve as a premise for mathematical reasoning skills (Tosto et al., 2014 ). On the other, spatial abilities and mathematics would be based on shared underlying processes (see Hubbard et al., 2005 ). A large series of previous studies revealed that children and adults who perform better on spatial tasks also perform better on tests of mathematical ability (Cheng & Mix, 2014 ; Holmes et al., 2008 ; Worrell et al., 2020 ). Focusing on young children, Mix et al. ( 2016 ) enrolled 854 children (5–13 years old), revealing that different spatial abilities are associated with better mathematical performance in a time‐dependent manner during early and late childhood. Indeed, while mental rotation is the best predictor of mathematical performance in kindergarten, visuospatial working memory is the best in sixth grade (i.e., 11–12 years old). However, the link between spatial abilities and mathematics is robust throughout the entire school age, from kindergarten to 12th grade (i.e., 17–18 years old), with performance in mental rotation tasks serving as the best predictor of mathematical skills (Lachance & Mazzocco, 2006 ; Thompson et al., 2013 ). The strength of such a link made researchers explore whether interventions on visuospatial abilities transfer to mathematical skills. Wolfgang et al. ( 2001 ) found that preschool children who engage in more block play perform better in school math, even if this effect appears only during high school. Similar findings were also reported by Mix and Cheng ( 2012 ).

A tight relation also exists between FR and mathematics. This is not surprising (McGrew & Hessler, 1995 ; Taub et al., 2008 ), considering that FR and math problems engage common underlying cognitive processes and sustain the ability to account for multiple relations among the components of a problem (Halford et al., 1998 ; Miller Singley & Bunge, 2014 ).

The correlative analyses conducted at T2 indicated that our training's major outcomes were significantly associated with mathematics and working memory. Its association with visuospatial abilities has been witnessed by previous behavioral and neuroimaging reports (Kyttälä & Lehto, 2008 ; Levin et al., 2005 ; Shah & Miyake, 1996 ), and analog parallelisms have been shown between working memory and FR (see for a review Yuan et al., 2006 ). The correlative analyses aimed to confirm the existence of the abovementioned relation in our sample. As this was the case, we can hypothesize to have induced indirect yet beneficial effects on these domains.

CONCLUSIONS AND LIMITATIONS

We designed an intervention capable of enhancing emerging cognitive functions like FR and visuospatial abilities, further sustaining their maintenance over time. Moreover, the correlations with visuospatial working memory and mathematical skills suggest a secondary effect on other cognitive domains. The proposed intervention is relatively easy to be conducted with preschool children; it stresses their natural cooperative attitude, is embedded into a play‐like context promoting motivation and compliance, and, more importantly, stimulates different cognitive domains simultaneously. Thus, even in the daily preschool practice, it seems well suited to accompany young children toward the potentiation of emerging skills and the acquisition of new ones fundamental for their future learning and discoveries.

A strength of our study was that sampling was not limited to a pre‐post design but rather envisioned a longitudinal evaluation carried out at three times (T0, T1, and T2) on all children. However, the results should also be considered against the limitations of the study. The first limitation of our study regards the poor sensitivity of the Imitating hand position subtest (IH) in measuring fine motor abilities. The choice of each test was guided by the need to keep the overall testing duration reasonable. Classical neuro‐motor evaluations generally require a long time to be administered. However, indexing fine motor skills in preschool children is fundamental given their relevance in later development. For this reason, future studies should consider adopting neuropsychological or neurological tests more sensitive to fine‐motor abilities (see Movement Assessment Battery for Children—Second Edition, Henderson et al., 2007 ).

The second limitation concerns the lack of mathematical and working memory assessment at T0 and T1, impeding us from investigating whether our training indirectly enhanced these functions. Beyond the temporal constraint mentioned above, it is worth noting that the Tedi‐Math is indicated for children of 4 years or older. As half of our initial sample was younger than 4, Tedi‐Math would have provided disputable results at T0 or T1. Future studies could face this point by selecting different evaluation tests.

One could wonder whether a larger sample size would have returned stronger results. While we cannot discard this point, most statistical comparisons indicated significant effects and at least moderate effect sizes. Negative findings, on the contrary, appear not related to an insufficient sample size but rather to biases in the experimental design. A valid argument instead would be that all children have been recruited in the same town. Larger recruitment, possibly including children from different regions, could grant more reliable and generalizable results. No prejudice, however, stands against the applicability of our findings to other regions, indicating a good generalizability to different geographic contexts. On the contrary, a larger sample would likely have participants with different socio‐demographic backgrounds (information not collected in our study), highlighting its potentially modulatory role on training effectiveness. In summary, we cannot neglect that we recruited a good sample size yet narrow in several factors impacting the children's cognitive development. A much larger sampling exploring multiple backgrounds, different IQ levels (e.g., below‐average, average, and above‐average), and socio‐demographic conditions would be fundamental to make our findings generalizable for preschoolers.

As evaluation had to be applied to children since 3 years old, a non‐verbal IQ test was identified. Besides, it had to be different from the Raven test that would have served later in the evaluation. However, it is well‐documented how the Leiter‐R test overestimates IQ scores relative to other standard tests (Grondhuis & Mulick, 2013 ), possibly due to the non‐verbal nature of the requested items. This aspect has to be carefully accounted for in the data analysis and their interpretation against reference values.

Finally, the two interventions allowed us to isolate effects specifically driven by modular toys. Still, children could have been attracted differently by the interaction with modular or plush toys. The whole experimental design was kept identical for the two groups, including the characters of the toys, just to minimize this potentially confounding effect. For future applications, it would be recommended to collect data concerning children's engagement into the different arms of the intervention, thus verifying their substantial homogeneity.

CONFLICT OF INTEREST

The authors declare no competing interests.

AUTHOR CONTRIBUTION

V.G., M.F.‐D., and G.R. designed the experiment. V.G., M.C.B., C.M., and P.P. performed data acquisition and analyses. V.G., M.F.‐D., and G.R. interpreted the results and wrote the paper. All authors have contributed to, seen, and approved the manuscript.

Supporting information

Supplementary Material

ACKNOWLEDGMENTS

The research was carried out thanks to the financial support of “Soremartec Italia Srl” (Alba, Cuneo, Italy). We thank Dr. Pietro Avanzini for his important supervision, statistical help, and comments on the manuscript. We also thank Prof. Ilaria Berteletti for her comments and indications on former versions of the manuscript. Open Access Funding provided by Consiglio Nazionale delle Ricerche within the CRUI‐CARE Agreement.

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[Correction added on May 14, 2022, after first online publication: CRUI‐CARE funding statement has been added.]

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• A-Z Publications

Annual Review of Psychology

Volume 62, 2011, review article, the development of problem solving in young children: a critical cognitive skill.

• Rachel Keen 1
• View Affiliations Hide Affiliations Affiliations: Department of Psychology, University of Virginia, Charlottesville, Virginia 22904; email: [email protected] * *Photograph by Cat Thrasher
• Vol. 62:1-21 (Volume publication date January 2011) https://doi.org/10.1146/annurev.psych.031809.130730
• First published as a Review in Advance on September 03, 2010
• © Annual Reviews

Problem solving is a signature attribute of adult humans, but we need to understand how this develops in children. Tool use is proposed as an ideal way to study problem solving in children less than 3 years of age because overt manual action can reveal how the child plans to achieve a goal. Motor errors are as informative as successful actions. Research is reviewed on intentional actions, beginning with block play and progressing to picking up a spoon in different orientations, and finally retrieving objects with rakes and from inside tubes. Behavioral and kinematic measures of motor action are combined to show different facets of skill acquisition and mastery. We need to design environments that encourage and enhance problem solving from a young age. One goal of this review is to excite interest and spur new research on the beginnings of problem solving and its elaboration during development.

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• Second Opinion

Cognitive Development in the Teen Years

What is cognitive development.

Cognitive development means the growth of a child’s ability to think and reason. This growth happens differently from ages 6 to 12, and from ages 12 to 18.

Children ages 6 to 12 years old develop the ability to think in concrete ways. These are called concrete operations. These things are called concrete because they’re done around objects and events. This includes knowing how to:

Combine (add)

Separate (subtract or divide)

Order (alphabetize and sort)

Transform objects and actions (change things, such as 5 pennies = 1 nickel)

Ages 12 to 18 is called adolescence. Kids and teens in this age group do more complex thinking. This type of thinking is also known as formal logical operations. This includes the ability to:

Do abstract thinking. This means thinking about possibilities.

Reason from known principles. This means forming own new ideas or questions.

Consider many points of view. This means to compare or debate ideas or opinions.

Think about the process of thinking. This means being aware of the act of thought processes.

How cognitive growth happens during the teen years

From ages 12 to 18, children grow in the way they think. They move from concrete thinking to formal logical operations. It’s important to note that:

Each child moves ahead at their own rate in their ability to think in more complex ways.

Each child develops their own view of the world.

Some children may be able to use logical operations in schoolwork long before they can use them for personal problems.

When emotional issues come up, they can cause problems with a child’s ability to think in complex ways.

The ability to consider possibilities and facts may affect decision-making. This can happen in either positive or negative ways.

Types of cognitive growth through the years

A child in early adolescence:

Uses more complex thinking focused on personal decision-making in school and at home

Begins to show use of formal logical operations in schoolwork

Begins to question authority and society's standards

Begins to form and speak his or her own thoughts and views on many topics. You may hear your child talk about which sports or groups he or she prefers, what kinds of personal appearance is attractive, and what parental rules should be changed.

A child in middle adolescence:

Has some experience in using more complex thinking processes

Expands thinking to include more philosophical and futuristic concerns

Often questions more extensively

Often analyzes more extensively

Thinks about and begins to form his or her own code of ethics (for example, What do I think is right?)

Thinks about different possibilities and begins to develop own identity (for example, Who am I? )

Thinks about and begins to systematically consider possible future goals (for example, What do I want? )

Thinks about and begins to make his or her own plans

Begins to think long-term

Uses systematic thinking and begins to influence relationships with others

A child in late adolescence:

Uses complex thinking to focus on less self-centered concepts and personal decision-making

Has increased thoughts about more global concepts, such as justice, history, politics, and patriotism

Often develops idealistic views on specific topics or concerns

May debate and develop intolerance of opposing views

Begins to focus thinking on making career decisions

Begins to focus thinking on their emerging role in adult society

How you can encourage healthy cognitive growth

To help encourage positive and healthy cognitive growth in your teen, you can:

Include him or her in discussions about a variety of topics, issues, and current events.

Encourage your child to share ideas and thoughts with you.

Encourage your teen to think independently and develop his or her own ideas.

Help your child in setting goals.

Challenge him or her to think about possibilities for the future.

Compliment and praise your teen for well-thought-out decisions.

Help him or her in re-evaluating poorly made decisions.

If you have concerns about your child's cognitive development, talk with your child's healthcare provider. 

Related Links

• Brain and Behavior
• Child and Adolescent Mental Health
• The Growing Child: School-Age (6 to 12 Years)
• Understanding the Teen Brain
• Topic Index

Related Topics

Adolescent Growth and Development

Cognitive Development in Adolescence

Growth and Development in Children with Congenital Heart Disease

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Problem-Solving Strategies and Obstacles

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• Application
• Improvement

From deciding what to eat for dinner to considering whether it's the right time to buy a house, problem-solving is a large part of our daily lives. Learn some of the problem-solving strategies that exist and how to use them in real life, along with ways to overcome obstacles that are making it harder to resolve the issues you face.

What Is Problem-Solving?

In cognitive psychology , the term 'problem-solving' refers to the mental process that people go through to discover, analyze, and solve problems.

A problem exists when there is a goal that we want to achieve but the process by which we will achieve it is not obvious to us. Put another way, there is something that we want to occur in our life, yet we are not immediately certain how to make it happen.

Maybe you want a better relationship with your spouse or another family member but you're not sure how to improve it. Or you want to start a business but are unsure what steps to take. Problem-solving helps you figure out how to achieve these desires.

The problem-solving process involves:

• Discovery of the problem
• Deciding to tackle the issue
• Seeking to understand the problem more fully
• Researching available options or solutions
• Taking action to resolve the issue

Before problem-solving can occur, it is important to first understand the exact nature of the problem itself. If your understanding of the issue is faulty, your attempts to resolve it will also be incorrect or flawed.

Problem-Solving Mental Processes

Several mental processes are at work during problem-solving. Among them are:

• Perceptually recognizing the problem
• Representing the problem in memory
• Considering relevant information that applies to the problem
• Identifying different aspects of the problem
• Labeling and describing the problem

Problem-Solving Strategies

There are many ways to go about solving a problem. Some of these strategies might be used on their own, or you may decide to employ multiple approaches when working to figure out and fix a problem.

An algorithm is a step-by-step procedure that, by following certain "rules" produces a solution. Algorithms are commonly used in mathematics to solve division or multiplication problems. But they can be used in other fields as well.

In psychology, algorithms can be used to help identify individuals with a greater risk of mental health issues. For instance, research suggests that certain algorithms might help us recognize children with an elevated risk of suicide or self-harm.

One benefit of algorithms is that they guarantee an accurate answer. However, they aren't always the best approach to problem-solving, in part because detecting patterns can be incredibly time-consuming.

There are also concerns when machine learning is involved—also known as artificial intelligence (AI)—such as whether they can accurately predict human behaviors.

Heuristics are shortcut strategies that people can use to solve a problem at hand. These "rule of thumb" approaches allow you to simplify complex problems, reducing the total number of possible solutions to a more manageable set.

If you find yourself sitting in a traffic jam, for example, you may quickly consider other routes, taking one to get moving once again. When shopping for a new car, you might think back to a prior experience when negotiating got you a lower price, then employ the same tactics.

While heuristics may be helpful when facing smaller issues, major decisions shouldn't necessarily be made using a shortcut approach. Heuristics also don't guarantee an effective solution, such as when trying to drive around a traffic jam only to find yourself on an equally crowded route.

Trial and Error

A trial-and-error approach to problem-solving involves trying a number of potential solutions to a particular issue, then ruling out those that do not work. If you're not sure whether to buy a shirt in blue or green, for instance, you may try on each before deciding which one to purchase.

This can be a good strategy to use if you have a limited number of solutions available. But if there are many different choices available, narrowing down the possible options using another problem-solving technique can be helpful before attempting trial and error.

In some cases, the solution to a problem can appear as a sudden insight. You are facing an issue in a relationship or your career when, out of nowhere, the solution appears in your mind and you know exactly what to do.

Insight can occur when the problem in front of you is similar to an issue that you've dealt with in the past. Although, you may not recognize what is occurring since the underlying mental processes that lead to insight often happen outside of conscious awareness .

Research indicates that insight is most likely to occur during times when you are alone—such as when going on a walk by yourself, when you're in the shower, or when lying in bed after waking up.

How to Apply Problem-Solving Strategies in Real Life

If you're facing a problem, you can implement one or more of these strategies to find a potential solution. Here's how to use them in real life:

• Create a flow chart . If you have time, you can take advantage of the algorithm approach to problem-solving by sitting down and making a flow chart of each potential solution, its consequences, and what happens next.
• Recall your past experiences . When a problem needs to be solved fairly quickly, heuristics may be a better approach. Think back to when you faced a similar issue, then use your knowledge and experience to choose the best option possible.
• Start trying potential solutions . If your options are limited, start trying them one by one to see which solution is best for achieving your desired goal. If a particular solution doesn't work, move on to the next.
• Take some time alone . Since insight is often achieved when you're alone, carve out time to be by yourself for a while. The answer to your problem may come to you, seemingly out of the blue, if you spend some time away from others.

Obstacles to Problem-Solving

Problem-solving is not a flawless process as there are a number of obstacles that can interfere with our ability to solve a problem quickly and efficiently. These obstacles include:

• Assumptions: When dealing with a problem, people can make assumptions about the constraints and obstacles that prevent certain solutions. Thus, they may not even try some potential options.
• Functional fixedness : This term refers to the tendency to view problems only in their customary manner. Functional fixedness prevents people from fully seeing all of the different options that might be available to find a solution.
• Irrelevant or misleading information: When trying to solve a problem, it's important to distinguish between information that is relevant to the issue and irrelevant data that can lead to faulty solutions. The more complex the problem, the easier it is to focus on misleading or irrelevant information.
• Mental set: A mental set is a tendency to only use solutions that have worked in the past rather than looking for alternative ideas. A mental set can work as a heuristic, making it a useful problem-solving tool. However, mental sets can also lead to inflexibility, making it more difficult to find effective solutions.

How to Improve Your Problem-Solving Skills

In the end, if your goal is to become a better problem-solver, it's helpful to remember that this is a process. Thus, if you want to improve your problem-solving skills, following these steps can help lead you to your solution:

• Recognize that a problem exists . If you are facing a problem, there are generally signs. For instance, if you have a mental illness , you may experience excessive fear or sadness, mood changes, and changes in sleeping or eating habits. Recognizing these signs can help you realize that an issue exists.
• Decide to solve the problem . Make a conscious decision to solve the issue at hand. Commit to yourself that you will go through the steps necessary to find a solution.
• Seek to fully understand the issue . Analyze the problem you face, looking at it from all sides. If your problem is relationship-related, for instance, ask yourself how the other person may be interpreting the issue. You might also consider how your actions might be contributing to the situation.
• Research potential options . Using the problem-solving strategies mentioned, research potential solutions. Make a list of options, then consider each one individually. What are some pros and cons of taking the available routes? What would you need to do to make them happen?
• Take action . Select the best solution possible and take action. Action is one of the steps required for change . So, go through the motions needed to resolve the issue.
• Try another option, if needed . If the solution you chose didn't work, don't give up. Either go through the problem-solving process again or simply try another option.

You can find a way to solve your problems as long as you keep working toward this goal—even if the best solution is simply to let go because no other good solution exists.

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Stewart SL, Celebre A, Hirdes JP, Poss JW. Risk of suicide and self-harm in kids: The development of an algorithm to identify high-risk individuals within the children's mental health system . Child Psychiat Human Develop . 2020;51:913-924. doi:10.1007/s10578-020-00968-9

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By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Supporting Cognitive Development: Experiences and Activities

In this lesson, you will learn the importance of providing children with a variety of age-appropriate experiences. This lesson describes how you can engage children in activities to promote cognitive development and address the individual needs of all learners.

• Identify examples of types of learning that take place across various age and ability levels.
• Explore your own values and assumptions about how and what children learn.
• Create experiences and activities that you can use with the children in your care.

You most likely serve a diverse group of children in your family child care home and, in turn, address a variety of needs and interests. You know that children’s cognitive development is important, so you plan your environment and daily activities to support their learning. Your understanding of what skills are typical for children of certain ages, what is interesting and appropriate for an individual child, and what is valued by families and the community affects your daily interactions with the children in your care (Bredecamp & Copple, 2009). Developmentally appropriate practice is a term used to describe educational and caregiving methods that promote each child’s optimal learning and development through a strengths-based approach to joyful, engaged learning. You can implement developmentally appropriate practice by recognizing the multiple assets all young children bring to the group as unique individuals and as members of families and communities (NAEYC, 2019). You should use this knowledge to make daily decisions about the learning experiences you offer children.

Experiences and Activities that Promote Infants’ and Toddlers’ Cognitive Development

Infants and toddlers learn best through daily interactions with warm, caring adults and play-based experiences. Play helps children develop their approaches toward learning. Memory, spatial awareness, problem solving, attention, and persistence are a few cognitive competencies developed through play. Families and caregivers can support children in becoming better learners by engaging in play with them.

It is important to remember that young children are natural explorers. They are hungry for information about the world around them. Children are learning how to learn. Adults can nurture this curiosity by promoting exploration and problem-solving. This helps young children develop thinking skills. There is a lot you can do to help young children learn. Here is a short list of ways to support infants and toddlers in your care: 

• Model your own thinking skills. Show interest, ask questions, and make comments about your observations as you play with children. For example, you might say, “Hmm. I really wanted to paint this part of my picture purple, but the purple paint is being used. What should I do?”
• Find opportunities throughout the day to play “What if…?” games. Ask the children questions like, “I wonder what sound this drum will make if I bang on it?” or “What if we run out of snack? What should we do?”
• Give children lots of chances to explore concepts. Read books and promote literacy development during individual and group activities, sing songs about the stories you read, and encourage children to imitate story characters with sounds or movements.

Consider the following ways in which young children learn important concepts through play (Guyton, 2011). You might notice that many of these examples involve learning in more than one area, or developmental domain. Developmental domains represent specific aspects of a child’s overall development (Cognitive, Motor, Language &Literacy, Social-Emotional, Physical Well-Being). It is important to keep in mind that, during play, children often learn across multiple developmental domains. You may also notice that these examples reflect everyday experiences, which offer many opportunities for learning.

• When a young infant interacts with a mobile by reaching for an item or visually tracking a moving item, they are learning about the important concept of cause and effect while at the same time improving their eye-hand coordination. 
• When a pre-toddler interacts with books, they are engaging in early literacy, as well as learning the names of objects or characters on book pages. 
• When a toddler uses a puppet to tell a story or act out happenings in the story they are learning to use their imagination, abstract thinking, and language. 

Experiences and Activities that Promote Preschool-Age Children’s Cognitive Development

As children move into the ages of 3 to 5 years, their knowledge and skills continue to develop each day. Observing the children you care for helps you learn about their unique interests and strengths. You can use your knowledge of child development and your observations about the individual children in your care to plan developmentally appropriate activities to promote cognitive development.

Much of preschoolers’ learning occurs through their interaction and their experiences with materials and the environment. Preschool children’s cognitive learning falls into several categories or content areas including: math, science, social studies, language and literacy, art, and technology. You can support children’s learning across these content areas. Here are a few examples of ways children might learn important concepts:

• Math: A preschool child notices what comes next in a pattern. A child notices that his friend has a different number (size) on his shoe.
• Science: A child uses her senses to explore a new food offered at lunch. Another child shares information about her pet and what food her pet likes to eat.
• Social studies: A child brings his baby pictures and takes on family roles in the dramatic play area. Children draw a map of the buildings they passed on a walk to the park.
• Language and literacy: A child sings rhyming songs and claps the syllables in words. A child spends time after nap relaxing and looking at pictures in books.
• Art: A child creates a three-dimensional sculpture of the bird house he sees in your backyard. Another child dances to music and pats a rhythm on a toy drum.
• Technology: A child uses a computer to create a message and artwork for his mother. 

You may notice that many of the above examples involve learning in more than one area. It’s important to keep in mind that, during play, children often learn across multiple domains. For example, when a child types a message to his mother on the computer, he is learning about technology and literacy. When a child claps along to a rhyming song, she may be learning literacy, math, and music. Everyday experiences offer preschool children many opportunities for learning.  Some examples of ways you can support preschooler’s cognitive development in your family child care include:

• Taking clipboards and markers outside to observe, draw and write about nature
• Planting seeds, discussing what they need to grow and observing how they change as they grow
• Exploring prisms and transparent objects on a light table
• Rolling cars or balls down ramps of different inclines to see how far they travel
• Mixing different colors of paints to create new colors
• Creating a graph of children’s favorite colors, season, food, or sports as a group
• Using measuring cups and funnels to fill containers with sand in the sensory table
• Exploring parts of a flower with magnifying glasses
• Setting up dramatic play so that children can pretend to cook, be doctors, make grocery lists, or take care of baby dolls
• Sorting plastic animals by different characteristics (size, shape, color)
• Listening and acting out stories like “The Three Little Pigs”
• Creating patterns by using colored blocks and pattern pictures
• Drawing maps or driving toy cars along maps or roads
• Creating classroom rules together as a group
• Sorting objects into groups, counting how many are in each group or identifying which group has less or more

Preschoolers are naturally curious and eager to explore.  As a family child care provider you can nurture their curiosity and promote thinking skills. Observe the children in your care, note what they are interested in and provide opportunities for exploration. You can use everyday materials and objects to help children learn about their world. Here are just a few examples of ways you can support preschool children’s learning:

• Model your own thinking and ask children to generate ideas. “I wonder how I can attach this hook on the wall. What are some ideas you have for attaching it?”
• Find opportunities to use language to facilitate children’s mathematical thinking. “I have four bananas, but we have six children to eat a snack. I wonder how we can make sure everyone has a part of a banana.”
• Give children many opportunities to explore concepts. Play games during transition to outdoors by asking children to get their coats based on some characteristics: “Everyone who is wearing a blue shirt can get their coat.”
• Encourage children to use self-control and acknowledge when they do.  Say things like, “I know you were working really hard on that structure. It is hard to stop, but your mom is here. How about we put a sign on your structure and save it for tomorrow?” 

Experiences and Activities that Promote School-Age Children’s Cognitive Development

Caring for school-age children in your family child care setting means offering experiences and activities that they enjoy. Again, observing the children and watching what their interests are can help with planning meaningful activities for school-age children. At this age, children may be learning to read, write, do math problems, search the internet for research reports, and conduct simple science experiments. Talking with children about what they are learning in school may help you collect interesting books, materials, games, and software that appeal to children. Here are a few examples of ways school-age children might learn important concepts:

Reading & Writing

Reading and writing opportunities help school-age children and youth to develop the skills and knowledge to effectively communicate information, ideas, and opinions to a variety of audiences.  Learning to write, like reading, is a lifelong process. Research has shown that when students receive writing instruction, their reading fluency and comprehension improve. You can support school-age children’s reading and writing skills by offering the following opportunities in your family child care home:

• Partner reading: School-age children are learning to communicate with others through reading and writing. Supporting reading and writing in your family child care home may include asking school-age children to read aloud to a friend or to one of the younger children. Partner reading not only helps readers build their ability to read smoothly (i.e., fluency), but it encourages children to work together (Armbruster, Lehr, & Osborne, 2001). 
• Reader’s theater: Acting out a story gives children the opportunity to work together to bring a book to life. Children at play naturally create characters, scenes, and stories. Dramatic play experiences encourage emotional growth, motivation, and engagement (Prescott, 2020). Reader’s theater is a form of dramatic play that effectively builds reading fluency by encouraging listening and speaking skills and boosting comprehension.
• Book discussions or literature circle: Literature circles help children and youth think and talk about the books they have read with other peers. Children can build a sense of community, deepen their understanding of books, and learn speaking and listening skills through these conversations.
• Creative writing activities: Younger children benefit from daily writing experiences, so embedding writing in the daily curriculum, such as having students write about their day, is helpful. Older children might benefit from writing-focused activities such as writing poems, writing letters to pen pals, writing autobiographies, writing songs, writing and acting out plays, and writing book reports on a topic of interest. Provide paper of different colors, sizes, and textures. Read poems and have children write their own poems, stories, and books, and illustrate them with photos (drawn and digital). 
• Author’s chair: Children take turns reading books they have written to their friends. You can designate a special chair and make this a weekly activity.

Mathematics

You can help school-age children become confident and successful mathematicians by planning math activities in your family child care setting. Here are just a few examples:

• Make math visual and hands-on . Many school-age children have difficulties picturing numbers and calculations in their minds. Active, hands-on learning opportunities provide students ways to visualize math concepts. For young children, addition and subtraction problems can be simplified by counting actual objects. Children can practice geometry by using toothpicks and marshmallows, for example, to create different types of shapes and angles. Older children can practice mathematical concepts by designing towers using building blocks or Legos and measuring them with tape measures, yardsticks, or rulers. 
• Create engaging opportunities for learning . If an activity relates to children’s lives, interest, or hobbies, then their level of participation and effort will increase. Sports, board games, card games, and videos can incorporate aspects of math. One example is for children to take a poll, asking the other children and their family members their favorite animal or food item. Then, children can create a graph to show the results of their poll. 
• “I'm noticing a pattern here, what patterns do you see?“
• “How did you figure that out?”
• “How did you solve this problem?”
• “What would happen if ...?”
• “Tell me more about this.”

Science and Exploration

Children are natural explorers who use all of their senses to investigate their surroundings. The enthusiasm and energy that children bring to new experiences provides a wealth of opportunities for learning. Opportunities for exploration and problem solving are tied with the physical world, the life sciences, earth and the environment. A fallen bird’s nest, the illumination of lightning bugs, the presence of pollution and litter are just a few examples of topics that can be used for deeper exploration. Growing plants, collecting rocks, finding insects, or creating a book about different birds seen in the neighborhood are all ways to engage children in science. Activities such as a walk to the park or a trip to the public library can help children make and document new discoveries.

Social Studies

You can make social studies come alive by creating opportunities for experiential learning. Experiential learning simply means to learn by doing. Experiential learning is a successful teaching strategy that enables children to learn and retain information through experiences tied to their learning. When engaged in experiential learning, children draw on all their senses. They read and listen to information to develop background knowledge. Children can see items or visuals related to a particular topic. They can take on roles to experience the topic they are learning about (Diem, 2004). 

Many social studies topics can be taught through experiential learning. For example, children studying a particular culture can perform tasks that individuals from that culture may typically perform (e.g., trading goods and services; designing transportation for a country; creating a mock election). The children can work together and with you to design engaging and meaningful learning around social studies.

Addressing the Needs of Diverse Learners and Families

All children need a strong developmentally appropriate curriculum, supportive environment, and nurturing relationships. As a family child care provider, you will need to plan experiences and activities that address the varying developmental needs of the children you serve. Some children you care for will thrive even without much support from you while other children will need your help more frequently.  It is critical that you work with each child’s family to learn more about their child’s learning and development and what supports have been most successful. Some children have specific learning needs and require individualized strategies to help them be successful in your child care home. Include an item asking about this on any paperwork you create as a “Getting to Know Your Child” form in your parent handbook. You will want to know about any special activities or equipment, specialists or programs that provide individualized strategies or services, and how your environment and daily activities can support the child’s optimal development.

Infants and toddlers (birth to three years) with disabilities may have an Individualized Family Service Plan (IFSP) that was written with the child’s parents and specialized therapists. Ask parents to share ideas and specific strategies about how you can best meet their child’s learning needs. Parents are the experts about their child. The more you know and understand each individual child’s developmental needs the better care you can support them. 

Children (three years and older) may have an Individualized Education Program (IEP) written with the child’s parents, teachers, and therapists. Ask the parents to share any information from their child’s IEP that will assist you in caring for the child. IEP’s may have specific strategies for learning new vocabulary, eliciting language, responding to questions, and following directions. When you can accommodate individual learning needs, you support the individual child as well as the other children in your care. Specialized learning strategies often are helpful not only for the child with special needs but for all the children in your family child care home.

Children who speak another language and are learning English are often called English language learners (ELLs) or dual language learners (DLLs). It might be hard for some children who are learning English to easily participate in all the activities in child care. The children learning English may be at different stages of acquiring their home language and English. Some children may hear quite a bit of English in their home, while others may hear none. This means some children may need more help than others. You can help children who are learning English by (a) including activities that are culturally meaningful to them, (b) giving them special supports, and (c) making children feel included in all activities. Helping all children is characterized by flexibility and a variety of changes. By making adaptations to the materials and/or the environment, or by adjusting your expectations of an activity, all children can feel successful and included.

Changes to Curricula

The curriculum should support the development and well-being of all children in a group to foster learning. While children may have diverse learning needs, the skills, and concepts they are learning through the curriculum may be similar.

Think about whether your experiences and activities include the right kind of goals and instruction for children. If not, you can make some changes to how information is presented. For example, some children who have difficulty with reading comprehension may need to have an abridged version of a book while other children can read the book in its entirety. Children with weak vocabulary skills might benefit from vocabulary instruction before reading a new book. School-age children can use a concept map where they write the vocabulary word, write the definition, identify an example and non-example, and draw a picture of the vocabulary word.

Changes to the Environment

You may have to make some changes to your family child care environment to meet the needs of all children. A school-age child may prefer reading while sitting on an exercise ball. Some children may prefer a self-monitoring chart (a list that children use to help know they are staying on task). Some children enjoy quiet classical music playing to help them stay focused on a game. In family child care, the mixed ages of children are an advantage when looking at the overall environment. Some school-age children with disabilities may enjoy playing in areas of your home child care that are designed for the younger children (e.g., an 8-year-old takes the role of the cashier in a pretend grocery store area). You may have to rethink the environment so that an older child can participate in more age-appropriate ways (e.g., make signs for the pretend store or count the play money so each preschooler has an equal amount). It is important to keep the environment age-appropriate and challenging for all the children in your care. You can do this by talking with parents about a child’s specific special needs and interests. Then, intentionally use the child’s interests to engage the child in planned activities.

Changes During Activities

Children with disabilities might find some activities very challenging. For example, a school-age child who is learning how to add numbers may have difficulty quickly adding up the points when playing a board game with other children. You can make the activity easier by providing this child with a basic calculator. You can decrease the use of a calculator as the child becomes faster at adding numbers on paper. The help and concrete support that you offer the child will change over time as they become more skilled. Making modifications to activities and offering individualized support allows all children to participate successfully in activities. As a family child care provider, it is your job to support all children. You should know the strengths and needs of all children in your care to ensure that each child gets what they need when they need it.

Partnering with Families

Always support children’s cultures, learning styles, and temperaments as you promote interesting and meaningful learning during daily routines and activities. Maintain open communication with children’s families about your philosophy about how children learn, the importance of the learning environment and planned daily activities. Encourage families to share their own thoughts and beliefs to ensure continuity of care. Additionally, by sharing your weekly schedule of activities and ways children are learning through the experiences with each family, you are demonstrating your commitment to their child’s development. 

The following video clips show caregivers supporting children’s cognitive development through various activities and interactions in their family child care setting.

Cognitive Development: Experiences & Activities

You promote learning through your interactions and careful planning of activities every day. You can support children’s cognitive development by:

• Providing a variety of enriching, developmentally appropriate activities that are challenging to each age level, but still allow them to feel successful.
• Presenting opportunities for toddlers, preschoolers, and school-age children to engage in active, project-based learning
• Offering interesting, age-appropriate play and exploration choices each day
• Providing books and videos that are fiction and nonfiction, culturally sensitive, and supportive of the interests of the children in your care
• Creating games and experiences that a variety of ages of children can participate in at their level of development
• Developing activity or curriculum plans that incorporate learning opportunities across all content areas (math, literacy, science, social studies, technology, art, music)
• Providing books, materials, toys, music, and foods that reflect the cultures of the children in your care
• Allowing for voluntary participation in activities knowing that not all children enjoy the same things
• Using daily observations and taking notes about the learning and development of each child you care for so you can best meet their individual needs

Each of us has different opinions, philosophies, and ideas about what and how children learn. Read and review the What Should Children Learn activity. Use these scenarios to reflect on your own point of view. Then think about how you would use your knowledge of cognitive development to respond to the adults in the scenarios. Write your responses and share them with your trainer, coach, or family child care administrator. Then compare your answers to the suggested responses. For this activity, it is helpful to consider multiple points of view when reflecting on the parents’ opinions and beliefs compared to your own. 

It is important to offer learning experiences and activities that are appropriate, engaging and supportive of children’s learning and development across various developmental domains including cognitive, social-emotional, physical, language and literacy, and creative development. Providers working toward their CDA credential should use the  CDA Science/Sensory Activity Plan and the CDA Mathematics Activity Plan handout to develop a science/sensory and a mathematics learning experience from your curriculum (or new activities you plan on implementing).  

What Should Children Learn During the Infant, Toddler, Preschool, and School-Age Years?

Cda science/sensory activity plan, cda mathematics activity plan.

Planning developmentally appropriate activities, experiences, and materials for your family child care home is important to supporting children’s play and exploration. Use the handout Materials and Activities You Use to Support Cognitive Development to think about how you support children’s cognitive development across a variety of ages.

Also, the Extension Database of Hands-On Activities for Child Care is an excellent resource, which includes experiences you can provide to a wide age-range of children: https://childcare.extension.org/hands-on-activities-for-child-care/

Materials and Activities to Support Cognitive Development

Demonstrate.

Child Care Aware of North Dakota. (2017). https://ndchildcare.org/providers/activities.html

Child Trends. (2019). Parental Expectations Increase Kids’ Stress. https://www.childtrends.org/videos/parental-expectations-increase-kids-stress  

Gestwicki, C. (2016). Developmentally Appropriate Practice: Curriculum and development in early education (6th ed.). Cengage Learning, Inc.

Graham, S., Bollinger, A., Booth Olson, C., D’Aoust, C., McArthur, C., McCutchen D., & Olinghouse, N. (2012). Teaching Elementary School Students to be Effective Writers: A practice guide (NCEE 2012-4058). National Center for Education Evaluation and Regional Assistance, Institute of Educational Sciences. 

Gurganus, S. P. (2007). Math Instruction for Students with Learning Problems (1st ed.). Pearson Education, Inc.

Guyton, G. (2011). Using Toys to Support Infant-Toddler Learning and Development. Young Children . https://educate.bankstreet.edu/cgi/viewcontent.cgi?article=1006&context=faculty-staff  

Harms, T., Cryer, D., & Clifford, R. (2007). Family Child Care Environment Rating Scale (rev. ed.). Teachers College Press.

National Association for the Education of Young Children (2019). NAEYC position statement on developmentally appropriate practice 2020. https://www.naeyc.org/resources/position-statements/dap

National Council of Teachers of Mathematics. (2014). Standards and Focal Points .

Olness, R. (2005). Using Literature to Enhance Writing Instruction . Newark, DE: International Reading Association.

Platas, L.M. (2017). Three for One: Supporting social, emotional, and mathematical development. Young Children, 72 (1), 33-37.

Prescott, J. (n.d.) The Power of Reader’s Theater: An easy way to make dramatic changes in kids’ fluency, writing, listening, and social skills. https://www.scholastic.com/teachers/articles/teaching-content/power-readerx2019s-theater/

Problem Solving

Your baby is learning how to get what she wants, when she wants it; this is also called thinking and problem solving.

During the first year of your baby’s life, she is making great strides in her ability to think, solve problems, and communicate with you. These are critical cognitive skills.

For instance, your baby thinks to herself, I want that rattle! Your baby solves the problem by deciding to roll over and reach for or crawl to the rattle. Maybe your baby is thinking, I am hungry! She solves the problem by communicating through cries, grunts, or pointing until you feed her.

Once you are sure your infant’s basic needs have been met and she is not in any danger, it is important to give your baby time to work on problem-solving skills.

Think about times you have just put your baby in the crib, and she immediately begins to cry as you turn to leave the room. Even though you may want to pick her up again and rock her longer, this is a great opportunity to let your infant work on her problem-solving skills, namely the skill of being able to self-soothe and see what she can do to make herself comfortable enough to go to sleep. It is certainly hard to listen to the cries, especially when it is your f irst baby, but as your baby matures, she will need to be able to put herself to sleep.

It is also very important to support problem-solving skills when your baby is learning to feed herself a bottle or use a spoon.

Infants as young as six months have been known to feed themselves; they won’t get all the food on the spoon or even in their mouths, but they are developing self-help skills and problem-solving skills. They are also developing their wrist muscles and fine motor skills (small muscle skills).

When you support problemsolving skills with your infant, you are supporting her brain development and giving her the power to think and constantly learn about the world around her.

Support your baby’s problem-solving skills by responding to her efforts to communicate. Use words to describe what she is experiencing: “I see you looking at the toy on the floor. Let me get that for you.” Talking to your child and explaining what you are doing when you do it also increases language development.

Your infant's problem-solving development:

0 to 2 months —Your infant is born with built-in problem-solving tools called reflexes (rooting and sucking for food).

2 to 4 months —Your infant is more alert; she explores; hand-eye coordination begins to develop and bringing toys to mouth leads to problem solving.

8 months —Your infant plays with toys to produce responses to actions by grasping, shaking, and banging.

12 months —Your baby uses more purposeful levels of problem solving and is no longer limited to what is immediately in front of her. She can now push a toy aside to choose another one.

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The development of problem solving in young children: a critical cognitive skill

Affiliation.

• 1 Department of Psychology, University of Virginia, Charlottesville, Virginia 22904, USA. [email protected]
• PMID: 20822435
• DOI: 10.1146/annurev.psych.031809.130730

Problem solving is a signature attribute of adult humans, but we need to understand how this develops in children. Tool use is proposed as an ideal way to study problem solving in children less than 3 years of age because overt manual action can reveal how the child plans to achieve a goal. Motor errors are as informative as successful actions. Research is reviewed on intentional actions, beginning with block play and progressing to picking up a spoon in different orientations, and finally retrieving objects with rakes and from inside tubes. Behavioral and kinematic measures of motor action are combined to show different facets of skill acquisition and mastery. We need to design environments that encourage and enhance problem solving from a young age. One goal of this review is to excite interest and spur new research on the beginnings of problem solving and its elaboration during development.

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ADAM & Mila

The Ultimate List of Creative Problem Solving Activities for Toddlers

We will explore problem solving skills, milestones and creative problem solving examples for kids that you will have fun trying with your little one.

Let’s Define Problem Solving

It’s simple. Problem solving is a skill set used by your baby that incorporates his or her ability to perceive, think, and gain understanding about his or her world; including remembering and decision-making. All of these problem solving skills are also known as cognitive skills .

Purposeful Problem Solving

Problem solving is a skill that begins early in your baby’s life. But there is a difference between simple problem solving and purposeful problem solving. Let’s explain.

Purposeful problem solving involves an intended action to achieve a desired result. Your child will use a specific problem solving approach to achieve this. They may include:

• Manipulating objects
• Learning about different properties of objects
• Learning how to get things done in the easiest way

Overcoming Obstacles

Overcoming obstacles is a necessity in becoming good at problem solving . There are times when you will be convinced that your child is a genius with the clever ways he can overcome the obstacles that stand in his way!

Everyday Problems and Solutions

Make way for your little creative thinker! Overcoming obstacles in clever ways is what your little one does best. These clever ways are not always verbal (especially at a younger age), it is important to practice nonverbal problem solving activities. So, what will your baby’s creative problem solving abilities look like? Take a look at two examples of problem solving life skills activities:

Life Problem: Your child sees her bottle sticking out of the diaper bag that is slightly out of reach. Solution: Your child pulls at the strap of the diaper bag to pull it closer to her.

Life Problem: Your child sees his favorite toy on the other side of the laundry basket. Solution: He crawls around the laundry basket to get his toy.

Understanding Cognitive Development

Cognitive development is your child’s ability to communicate, think, and problem solve. As your child grows, his or her brain is growing as well. As your child’s cognitive skills become more developed, the more he or she will begin to explore their world and test things in his or her environment. Understanding your baby’s cognitive development is key to chosing the best activities to help your baby master his or her problem solving skills.

Resist Coming to the Rescue

One great tip for parents is to not be so quick to come to the aid of your child when he or she faces small everyday problems. By allowing your baby the time and space to figure things out for himself, you help him build confidence and grow his ability to problem solve.

Tips for Easy Creative Problem Solving Activities

We at ADAM & Mila wish to provide practical and easy to apply ideas for fun and educational activities. There is a variety of easy brain boosting activities to stimulate your baby’s brain, increase his or her critical thinking skills , and help your little one become a great problem solver. There are a lot of activities that you can do with your child.

Problem Solving Activities For Infants

• Sing to your baby
• Read to your baby every day

Problem Solving Activities For Toddlers

• Play peek-a-boo
• Play hide-and-seek with objects
• Play with puzzles, blocks, or drawing materials

Problem Solving Activities For Children Age 2-3

• Sort objects by color, size, and shape
• Help your child “write” his own book by writing his words while he or she draws the pictures
• Teach the words; on, under, behind, around by playing games like Simon Says
• Provide a “dress-up” box for your child for imaginative play

The Milestones of Developing Methodical Problem Solving Skills

Below we have collected all the milestones your child will go through month-by-month as he or she acquire these critical problem solving skills.

That Second Reach

Development Milestone emerges from age 5 to 7 months.

At about 5 months old, your child will begin to purposely reach for second objects while still holding on to the first one. For example, while holding one toy in his hands, he may use his other hand to reach for a second toy. He does not, however, have to necessarily pick it up.

Works for It

Development Milestone emerges from age 5 to 9 months.

Now, your baby’s movements start to demonstrate clear purpose, intention, and persistence while repeatedly reaching for objects. This is when your child will try and try again to get that ball he really wants that is out of his reach. He may reach, stretch, or even wiggle to get it.

Drops Object to Pick Up New Object

Development Milestone emerges from age 6 to 8 months.

At this age, if your little one is holding an object or toy in each of her hands, she may drop one of them to pick up a new object without even thinking about it. She isn’t yet purposefully trying to think of a way to hold all three, which is why she will drop one toy to get the new one.

Reaches for New Object While Holding Two

Development Milestone emerges from age 8 to 10 months.

Unlike the stage before, this time when your child is holding an object in each of his hands, he will attempt to pick up a third one without dropping the ones he is already holding. There is a thought process of how to hold the third item, whether it is by adjusting his grasp on the current two items, reaching with his mouth for the third item or coming up with another way.

Pulling It Closer

Now, when your child sees his favorite toy resting on a towel or sheet out of reach, he will simply purposely pull the towel or sheet with the toy on it closer to him. Observe this milestone on your child by simply placing a toy on a towel on the floor and see what your child does.

Development Milestone emerges from age 8 to 11 months.

Nothing is going to stop your little one from getting to the toy he wants! Not a box, laundry basket, or pillow. At this age, your baby will figure out a way to get that toy he wants, even if he has to push, reach above, or move around something to get it.

Getting in Motion to Grab an Object

Development Milestone emerges from age 9 to 12 months.

Now, your child is ready to crawl, creep, scoot, roll, climb, or walk to get to that toy she wants! You can test to see if your child has mastered this milestone by placing a toy that has multiple pieces like a stacking toy around the room. Place the base of the stacking toy by your child and the rings around the room and watch as your child problem solves to find the rings and bring them back to the base.

Pulling Toy Horizontally by a Handle or Strap

This stage shows your child’s understanding of how two objects are connected and how one can influence the movement of the other. So, you may see your child pull at a shoestring to get her shoe or the strap of a diaper bag to get her bottle or sippy cup.

Pulling Toy Vertically by a Handle or Strap

Development Milestone emerges from age 13 to 15 months.

Now that she has mastered pulling horizontally at a string or strap of an object to bring it closer to her, she will begin to pull at strings or straps that are hanging to pull an object up to her. For example, she may pull a string or plastic chain link of a toy dangling from her high chair.

Flips Over Container to Get to Small Objects

Development Milestone emerges from age 12 to 18 months.

When trying to get at a small object inside of a container, your baby will likely try to get at it by poking his finger in it or shaking it. However, after showing him how, your baby will flip over the container and begin to shake it until the desired object falls out.

Simple Problem Solving with Tools

Development Milestone emerges from age 17 to 24 months.

At this stage, your child will use an unrelated object to get the object she actually wants. For example, she may grab a nearby stick (or spatula) to get her favorite toy out from underneath the couch or she may invent other ways to solve her problem of getting her favorite toy out.

Turning Doorknobs

Development Milestone emerges from age 21 to 23 months.

Now, the fun begins (depending on your idea of fun) because your toddler has figured out that he or she can get to the other side of the door by simply turning the doorknob. This means you need to do another round of baby proofing. A door is no longer an obstacle.

These are some of the many milestones that your child is mastering as he or she is growing from infant to toddler. Your baby’s ability to problem solve is an important one. It can also be a lot of fun to help them along the way as that skill continues to develop. It is important to note that every baby learns at his or her own pace. So, don’t worry if your baby isn’t doing what your neighbor’s kid was doing at that age. Always speak to your pediatrician for serious concerns. Otherwise, try out some fun activities with your baby that we know will benefit both you and your child. Oh, and remember to have fun!

We hope that this article was helpful to you. We would love to know what you think! Please share our article with others who might benefit from it.

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April 3, 2019 at 6:27 pm

Enjoyed reading your article on early childhood growth and thinking process for problem solving. Helpful

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Cognitive Behavioral Therapy

Solving problems the cognitive-behavioral way, problem solving is another part of behavioral therapy..

Posted February 2, 2022 | Reviewed by Ekua Hagan

• What Is Cognitive Behavioral Therapy?
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• Find a therapist who practices CBT
• Problem-solving is one technique used on the behavioral side of cognitive-behavioral therapy.
• The problem-solving technique is an iterative, five-step process that requires one to identify the problem and test different solutions.
• The technique differs from ad-hoc problem-solving in its suspension of judgment and evaluation of each solution.

As I have mentioned in previous posts, cognitive behavioral therapy is more than challenging negative, automatic thoughts. There is a whole behavioral piece of this therapy that focuses on what people do and how to change their actions to support their mental health. In this post, I’ll talk about the problem-solving technique from cognitive behavioral therapy and what makes it unique.

The problem-solving technique

While there are many different variations of this technique, I am going to describe the version I typically use, and which includes the main components of the technique:

The first step is to clearly define the problem. Sometimes, this includes answering a series of questions to make sure the problem is described in detail. Sometimes, the client is able to define the problem pretty clearly on their own. Sometimes, a discussion is needed to clearly outline the problem.

The next step is generating solutions without judgment. The "without judgment" part is crucial: Often when people are solving problems on their own, they will reject each potential solution as soon as they or someone else suggests it. This can lead to feeling helpless and also discarding solutions that would work.

The third step is evaluating the advantages and disadvantages of each solution. This is the step where judgment comes back.

Fourth, the client picks the most feasible solution that is most likely to work and they try it out.

The fifth step is evaluating whether the chosen solution worked, and if not, going back to step two or three to find another option. For step five, enough time has to pass for the solution to have made a difference.

This process is iterative, meaning the client and therapist always go back to the beginning to make sure the problem is resolved and if not, identify what needs to change.

Advantages of the problem-solving technique

The problem-solving technique might differ from ad hoc problem-solving in several ways. The most obvious is the suspension of judgment when coming up with solutions. We sometimes need to withhold judgment and see the solution (or problem) from a different perspective. Deliberately deciding not to judge solutions until later can help trigger that mindset change.

Another difference is the explicit evaluation of whether the solution worked. When people usually try to solve problems, they don’t go back and check whether the solution worked. It’s only if something goes very wrong that they try again. The problem-solving technique specifically includes evaluating the solution.

Lastly, the problem-solving technique starts with a specific definition of the problem instead of just jumping to solutions. To figure out where you are going, you have to know where you are.

One benefit of the cognitive behavioral therapy approach is the behavioral side. The behavioral part of therapy is a wide umbrella that includes problem-solving techniques among other techniques. Accessing multiple techniques means one is more likely to address the client’s main concern.

Salene M. W. Jones, Ph.D., is a clinical psychologist in Washington State.

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Enhancing cognitive dimensions in gifted students through future problem-solving enrichment programs

• Open access
• Published: 09 September 2024
• Volume 5 , article number  248 , ( 2024 )

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• Khaled Elballah 1 ,
• Norah Alkhalifah 2 ,
• Asma Alomari 2 &
• Amal Alghamdi 2  

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This study has undertaken a scrutiny of research pertaining to enrichment programs based on future problem-solving skills, aimed at enhancing the cognitive dimensions of gifted students between the years 2010 and 2023. The study used a sample of 10 studies; 3 correlational studies and 7 quasi-experimental studies. The study employed the descriptive-analytical approach by following a meta-analysis method. The study aimed to discern the effectiveness of enrichment programs based on future problem-solving skills in developing the cognitive dimensions of the gifted. The study's findings have indicated a significant impact of enrichment programs based on future problem-solving skills in the development of the cognitive dimensions of the gifted, as per both correlational and quasi-experimental designs. Moreover, statistically significant differences were found related to the variables of educational level and gender in accordance with both correlational and quasi-experimental designs. The study also advocates the need for further research in this domain to facilitate the generalization of the novel findings of this study within the gifted field.

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1 Introduction

The special needs of gifted students and the challenges they encounter compel us to offer them tailored education that aligns with their potential. According to relevant literature, numerous programs and practices are employed in educating gifted students. In recent years, gifted education has witnessed substantial growth in programs, providing students with various enrichment opportunities. Among these opportunities are enrichment programs that come in various forms, often interactive and centered around higher-order thinking skills. This allows students requiring additional intellectual stimulation to remain engaged and interested in their classrooms [ 3 ]. Enrichment programs focusing on future problem-solving skills are a significant component of gifted education. Many studies have called attention to such problem-based programs. Given the challenges faced by modern societies due to rapid and continuous changes, gifted individuals in the twenty-first century find it imperative to possess future problem-solving skills. These skills involve individuals actively exploring the future by connecting the past with the present, attempting to anticipate the future based on current information and data, and creating current and future solutions to these issues. Future thinking is an active process encompassing all situations, involving planning toward future objectives, passing through stages of imagination, prediction, visualization, planning, and decision-making [ 2 ].

Enrichment programs centered on future problem-solving skills focus on enhancing cognitive processes, such as creative thinking, critical thinking, future-oriented thinking, imaginative thinking, and motivation for achievement. These programs are suitable for experienced students and support the educational process interactively. Their curriculum encompasses essential steps that students should follow when solving future problems. These steps start with identifying future challenges, selecting the most prominent challenges, generating solutions and ideas, setting criteria and applying them, and conclude with developing an action plan, equipping students with the tools and strategies to address these problems [ 48 ]. In this regard, [ 20 , 33 ] underline the significance of future problem-solving enrichment programs in gifted education, emphasizing that it represents a novel and captivating approach for gifted students to enhance their self-efficacy, acclimate to higher-order thinking skills, and cultivate their creative self. This, in turn, improves their creative thinking, mitigates the potential for boredom and monotony, and broadens their knowledge while introducing them to new areas of interest. Johnsen [ 28 ] posits that gifted education programs must prioritize offering rich experiences characterized by depth, challenge, and flexibility. They should challenge the capabilities of gifted students and develop their higher-order thinking skills, focusing on holistic development of their mental, skill-based, emotional, and independent thinking capacities in problem-solving situations. Such characteristics can be found in enrichment programs that revolve around genuine future problems to nurture these skills.

Regarding research, several studies have directed their attention to exploring future problem-solving competencies. For instance, [ 20 ] assert the effectiveness of enrichment programs centered on future problem-solving in enhancing students' creative self-efficacy. Additionally [ 7 ], affirms the effectiveness of an enrichment program based on the Kolb model in developing problem-solving skills among gifted students in the cognitive dimensions.

On another side, studies have examined the characteristics of gifted students participating in future-thinking problem-based programs [ 55 ]. Conducted a study that revealed that children participating in a program based on diverse future-thinking skills acquired the ability for profound observation, extensive general knowledge, exceptional verbal, logical, detailed, and creative thinking, and a flexible approach to problem-solving. Despite the positive impact identified by numerous previous studies in the context of future problem-solving programs, there have been variations, particularly concerning gender, educational level, and other skills, as evidenced by the findings of certain studies [ 11 ]. Furthermore, this methodological approach has not garnered significant attention from researchers in Arab countries, despite the researchers' affirmation of the importance of sequential analyses [ 47 ]. Emphasize that Meta analyses can provide unique contributions to the field of gifted education. Firstly, the results are reliable, stemming from replicable methodological steps [ 25 ]. Secondly, by summarizing the current state of evidence, Meta analyses offer researchers the opportunity to place their insights within the larger context. Thirdly, Meta analyses allow researchers to examine the effects of a large number of independent variables and potential influences simultaneously [ 45 ]. Asserts that Meta analyses are a more comprehensive method for conducting program evaluations in gifted education, as it enables the study of a wide array of independent and moderating variables simultaneously, facilitating a better understanding of the results of various studies.

1.1 Research questions

This study employed a meta-analytic approach to synthesize findings concerning problem-solving skills in the domain of gifted education. The purpose was to address the following inquiries:

What is the effect size average of the impact of enrichment program interventions based on future problem-solving skills for gifted students in fostering their cognitive dimensions, according to correlational designs?

To what extent does the effect size average of the impact of enrichment program interventions targeting future problem-solving skills for gifted students vary in terms of their cognitive dimension development according to correlational designs, as a result of participant type (males, females, both) and educational level (elementary, middle, high school)?

What is the effect size average of the impact of enrichment program interventions based on future problem-solving skills for gifted students in fostering their cognitive dimensions, according to quasi-experimental designs?

To what extent does the average magnitude of the impact of enrichment program interventions targeting future problem-solving skills for gifted students vary in terms of their cognitive dimension development according to quasi-experimental designs, as a result of participant type (males, females, both) and educational stage (elementary, middle, high school)?

1.2 Significance of the study

The significance of this study resides in its substantive contribution to the field of gifted education research, mitigating the rare of studies employing such analytical methodologies. Furthermore, it answers the clarion call voiced by numerous scholars in the Arab world regarding the importance of conducting meta-analytical studies within the educational field [ 1 ]. This study will play a pivotal role in the realization of the directives set forth by the American Psychological Research Guide, which underscores the criticality of employing meta-analysis as an adjunctive statistical method for scrutinizing statistical significance. Through this meta-analysis, we shall elucidate the effective factors upon the education of gifted students. Consequently, it will bestow unparalleled contributions to the field of gifted education by means of descriptive multivariate analyses, which proffer a more comprehensive evaluation of gifted education programs. They empower researchers to scrutinize a wide spectrum of independent variables and moderating variables concurrently [ 50 ].This study will serve as the cornerstone upon which plans for the development and activation of the roles of gifted care programs in fostering cognitive dimensions are constructed. This is because any developmental blueprints hinge upon a comprehensive portrayal of the existing reality from all its facets. Moreover, this study will offer guidance for future research endeavors and inquiries into enrichment program typologies.

1.3 Research terminologies

1.3.1 meta-analysis.

This study uses the meta-analysis methodology, defined as statistical analysis for a comprehensive spectrum of research findings. Its principal objective resides in the synthesis of abstracts or information extracted from an expansive body of research, with the overarching intention of fostering cohesion among studies that share a common thematic concern. This methodological approach serves to facilitate a more profound understanding of the rapid proliferation of antecedent research endeavors. The nomenclature employed to signify meta-analysis has demonstrated a degree of lexical diversity, encompassing designations such as transcendental analysis and meta-analysis [ 15 ].

1.3.2 Enrichment programs

Enrichment programs, as defined by [ 6 ], refer to an assemblage of educational programs used by educators to nurture the development of students' competencies. These proficiencies encompass a varied spectrum, including cognitive aptitudes, social skills, and other skills that enhance the educational experiences of students.

1.3.3 Future problem-solving skills

Future problem-solving, as elucidated by [ 4 ], draws upon Torrance's (2003) definition of this term, characterizing it as the acumen employed for the analysis and formulation of strategies directed at the resolution of problems, challenges, or difficulties, and undefined obstacles projected to manifest in the future, extending over a temporal future of no less than twenty-five years.

1.3.4 Gifted students

The National Association for Gifted Children (NAGC) has defined gifted and talented students as those who perform—or can perform—at higher levels than others of the same age, experience, and environment in one or more areas. These talented people must modify their educational experience to learn and achieve their potential. Furthermore, gifted and talented students can have the following features:

They come from all ethnic and cultural groups and from all economic classes.

It requires obtaining adequate educational opportunities to achieve their potential.

May have learning and processing disorders that require specialized intervention and adaptation.

Need support and guidance to develop socially, emotionally and in different areas [ 35 ].

1.3.5 Cognitive dimensions

Cognitive dimensions, as expounded by [ 9 ], encompass an array of concepts, ideas, and systematically organized mental operations resident within a child's cognitive consciousness. These operations discriminate the cognitive realm and are predicated upon skills such as recall, categorization, and decision-making. These skills, in turn, are rooted in the skills of thinking, conceptualization, and organizational aptitude.

1.4 Study procedures

1.4.1 study design.

The study used the descriptive-analytical approach applying the meta-analysis method, as it was suitable for the nature of this study. Meta-analysis is considered an advanced approach for comprehensive summarization of previous studies and research. It significantly contributes to the interpretation of the huge literature that extends beyond the confines of academia. It is a descriptive-analytical methodology aimed at extracting underlying findings from multiple outcomes derived from individual studies with specific attributes. This involves conducting a survey of studies related to the subject matter of the study, examining their theoretical framework, as well as the research problem, hypotheses, procedures, and results. Subsequently, criteria were established for selecting studies that warrant reanalysis and the appropriate decisions [ 19 ].

1.4.2 Study sample

The sample comprised ten research articles published between 2010 and 2023 in diverse international journals.

Shokraneh [ 45 ] recommended documenting the strategies and steps employed in meta-analysis to facilitate repetition or new updates for meta-analysis. In this study, the analytical strategies and steps adopted were as follows:

2.1 Firstly, data collection

Studies published between 2010 and 2023 were included, using a two-stage process. The first stage involved conducting computer-based research using the following keywords: "gifted," "gifted education programs," "gifted education," "gifted student," "thinking skills," "future problem-solving skills," "gifted programs," "cognitive dimensions," "cognitive resilience," "decision-making," "achievement," and "metacognition." Studies that included these keywords in their titles or abstracts were initially selected and individually reviewed to identify additional references.

Manual searches were conducted across several journals, with articles related to gifted students, including but not limited to the Journal of Secondary, Journal for the Education of the Gifted, Roeper Review, Gifted Child Quarterly, Gifted Education, Journal of Advanced Academics, Journal of King Saud University, Journal of Umm Al-Qura University, International Journal of Educational Research at the United Arab Emirates University, Educational Journal at Taif University, and Dar Al-Mandhuma Database. Additionally, searches were conducted on the Google Scholar scientific researcher database, ERIC database, and the Google search engine. The previous search results yielded a total of 288 research articles. In the second stage, criteria for including studies in the current research were applied, resulting in a reduction to ten research articles.

2.2 Secondly, inclusion and exclusion criteria

The study applied inclusion criteria based on the following guidelines:

Selection of studies published between 2010 and 2023 in Arabic and foreign journals.

Selection of complete studies (open-access journals).

Selection of studies with clearly defined correlational or quasi-experimental methodologies.

Selection of studies that explicitly stated the sample size.

Selection of studies that employed educational tests as Pearson correlation coefficients, "t-tests," and "F-tests."

Selection of studies with available statistical data indicating the relationship between the interventions of enrichment programs based on future problem-solving skills for gifted students and the development of their cognitive dimensions or their impact (correlation coefficients, sample size, mean, standard deviation). The previous studies were examined, resulting in the inclusion of ten studies investigating the impact of enrichment program interventions based on future problem-solving skills for gifted students and the development of their cognitive dimensions, according to the criteria specified above. It is to be noted that articles removed during the systemic process included the duplicated articles, articles identified as ineligible for the research by the automation tools and other articles that were removed for some other reasons such as missing information or bad quality of the articles or irrelevant to the study topic. It is also important to note that 41 articles were excluded from the analysis because of the missing information or bad quality of the articles or irrelevant to the study topic.

3 PRISMA flow diagram of the systematic search

Figure 1 describes the process stages used to select the articles used in this research. It is to be noted that two sources have been used in the process of selecting of data namely articles from databases and registrars. Furthermore, it is to be noted that articles removed during the systemic process included the duplicated articles, articles identified as ineligible for the research by the automation tools and other articles that were removed for some other reasons such as missing information or bad quality of the articles or irrelevant to the study topic.

PRISMA flow diagram of the systematic search

Table 1 describes the studies in the research sample included in the meta-analysis.

3.1 Thirdly, the encoding of study characteristics

A coding protocol was established to reflect information regarding the principal attributes of the study, experimental conditions if applicable, and the participants and samples. The features of the outcomes [ 21 ]. Consequently, the encoding of the modified variables in the present study stands as follows:

3.1.1 A—Study design

The encoding of the study design was categorized into:

Correlational research: If these studies investigate the correlational relationship between interventions of enrichment programs for gifted students and the development of their cognitive dimensions.

Quasi-experimental research: If these studies explore the impact of enrichment programs based on future problem-solving skills for gifted students in developing their cognitive dimensions.

3.1.2 B—Participant type

The encoding of participant type was categorized as (males, females, males and females together).

3.1.3 C—Educational level

The encoding of educational stage was categorized as (elementary, middle, secondary).

3.2 Fourthly, data analysis strategy

The study used effect size criteria provided by [ 17 ], and in accordance with that, the effect size is categorized as follows: from 0 to 0.10 weak, from 0.11 to 0.30 modest, from 0.31–0.50 moderate, from 0.51to 0.80 large, and represents greater than 0.81 as very large.

Furthermore, the common effect size of previous studies was calculated by determining the model used and represented by the random or fixed-effects model, which is determined by the test of heterogeneity that detects whether the observed variance in effect sizes (Q) significantly differs from the variance due to sampling error [ 21 ]. Accordingly, it is necessary to find the value of Q and compare it to the degree of freedom value (df = n-1) in the Chi-square value tables as follows: If the value of Q is less than the Chi-square value, it is interpreted that the effect sizes of the studies are homogeneous, and the common effect size is calculated according to the fixed-effects model. However, if the value of Q is greater than the Chi-square value, it is interpreted that the effect sizes of the studies are not homogeneous, and the common effect size is calculated according to the random-effects model.

In the current study, the random-effects model was used to align with the study's objectives, and the test of heterogeneity was conducted, as well as the application of categorical moderator analysis to examine whether the common effect size of enrichment programs based on future problem-solving skills for gifted students in the development of their cognitive dimensions showed significant differences based on study type, participant type, and educational stage. Moreover, it was determined whether the moderator was significant based on the level of significance value (Q) in the light of the random-effects model.

3.3 Fifthly, effect size calculation

The effect size in quasi-experimental studies was calculated as the difference between the means of the experimental and control groups divided by the common standard deviation. Additionally, Pearson's correlation coefficient was used as a measure of effect size for correlational studies.

3.4 Sixthly, publication bias assessment

Publication bias refers to the irregular representation of studies published in the literature, resulting from a higher probability of publishing studies with significant effects. This bias can influence the results of meta-analysis [ 42 ]. Researchers in meta-analysis studies have examined a set of peer-reviewed scientific studies published in journals, although there are similar studies that have not had the opportunity to be published in those journals for one reason or another, raising doubts about the possibility of bias in the results they reach. Hence, the importance of assessing publication bias becomes evident. For this purpose, Egger's regression test was used, which is a test of regression analysis for non-symmetrical funnel plot. It relies on the value "t" and its significance, so if the "t" value is not significant, it indicates no bias.

3.5 Seventhly, heterogeneity assessment

Heterogeneity analysis is a common approach in meta-analysis. It examines the likelihood of observing the variation displayed by effect sizes if sampling error is what makes them different [ 21 ]. In the current research, heterogeneity was evaluated using the Cochran's Q test, and the I 2 statistic [ 27 ]. The Q statistic follows a Chi-square distribution with degrees of freedom (n-1), while the I 2 statistic represents a percentage of the total variation across studies attributed to heterogeneity rather than chance. The test also examines the null hypothesis of homogeneity, stating that all studies evaluate the same effect [ 27 ].

3.6 Data analysis

The researchers of the current study used the Comprehensive Meta-Analysis (CMA) V.3.3.07 software to analyze the data extracted from previous studies (n = 10).

4.1 First question results

“What is the effect size average of the impact of enrichment program interventions based on future problem-solving skills for gifted students in fostering their cognitive dimensions, according to correlational designs?"

To answer this question, the researchers used the following:

The heteroscedasticity test was employed to ascertain whether the observed variability in effect sizes within the research and study sample significantly deviated from the expected variability attributable to sampling error. This determination was crucial in identifying the appropriate model for aggregating effect sizes, as illustrated in Table  2 .

Table 2 clearly demonstrates the outcome of the heterogeneity test, which attests to its statistical significance (P = 0.037). The observed value stands at Q = 10.39 with degrees of freedom df = 2, markedly exceeding the critical Chi-squared (X 2 ) table value at a 95% confidence level. Furthermore, the heterogeneity ratio index (I 2  = 80.14%) underscores a substantial degree of heterogeneity among the various studies, indicating a dearth of common effect size. This, in turn, suggests a marked incongruity among the studies. Given the considerable variation in effect sizes across different studies, it is imperative to subject them to analysis in accordance with the random effects model. In this model, the common effect is construed as the mean value of these respective effects [ 16 ].

Moreover, the tabulated data in Table  2 unveil that the common effect size, as posited by the random effects model, is estimated at 0.531 with a standard error of 0.004 and a 95% confidence interval spanning from 0.317 to 0.694. This estimate is consistent with the characterization of a substantial effect size, as delineated by [ 17 ]. Consequently, the influence of enrichment programs tailored for intellectually gifted students, particularly concerning the development of their cognitive dimensions through the utilization of a correlational design, is indeed of considerable large.

In the assessment of publication bias, researchers employed the regression analysis test by Egger, yielding a coefficient "t" (1.15), with one degree of freedom, with P value of 0.455. This value bears no statistical significance, signifying the absence of publication bias.

4.2 Second question results

“To what extent does the effect size average of the impact of enrichment program interventions targeting future problem-solving skills for gifted students vary in terms of their cognitive dimension development according to correlational designs, as a result of participant type (males, females, both) and educational level (elementary, middle, high school)”

To answer this question the researchers used Analysis of Modified Variables, as follows:

The researchers employed a modified analysis to discern whether the impact of enrichment program interventions on the cognitive dimensions of gifted students varies depending on the type of participants (males, females, both), and the educational level (primary, middle, secondary). This revelation is elucidated through Table  3 .

It is evident from Table  3 that statistically significant disparities in the effect size of enrichment program interventions on the cognitive dimensions of gifted students are attributed to the gender of the participants (males, females, both), in favor of females (P = 0.004), and the educational stage (primary, middle, secondary), in favor of the secondary level (P < 0.001).

4.3 Third question results

“What is the effect size average of the impact of enrichment program interventions based on future problem-solving skills for gifted students in fostering their cognitive dimensions, according to quasi-experimental designs?”

An assessment of heterogeneity test was employed to ascertain whether the observed variability in effect sizes within the research and study sample significantly deviated from the expected variability attributable to sampling error. This determination was crucial in identifying the appropriate model for aggregating effect sizes, as illustrated in Table  4 .

Table 4 reveals that the heterogeneity test results signify significance (< 0.001 = p). The value (Q = 139.1) is accompanied by degrees of freedom (6), surpassing the critical Chi-squared value (X 2 ) and indicating a 95% confidence interval. Moreover, the heterogeneity ratio (I 2  = 96%) indicates a substantial degree of heterogeneity among studies. This suggests that the research and study samples do not share a common effect size, highlighting their inherent heterogeneity. Given the variation in effect sizes across studies, it is imperative to analyze them according to the random-effects model, where the common effect is the average of these effects [ 16 ]. Furthermore, Table  4 demonstrates that the common effect size, according to the random-effects model, is 0.745 with a standard error of 0.003 and a 95% confidence interval ranging from 0.436 to 0.789. This places the common effect size within the realm of substantial effect sizes, as indicated by [ 17 ]. Consequently, the impact of enrichment programs for gifted students on cognitive dimensions development, employing a quasi-experimental design, is large.

Publication Bias Assessment: The researchers employed Egger's regression analysis test, yielding a "t" value of 0.3211 with degrees of freedom (5) at a p- value 0.7623. This statistically non-significant value suggests an absence of publication bias.

4.4 Fourth question results

“To what extent does the average magnitude of the impact of enrichment program interventions targeting future problem-solving skills for gifted students vary in terms of their cognitive dimension development according to quasi-experimental designs, as a result of participant type (males, females, both) and educational stage (elementary, middle, high school)?”

To answer this question, the researchers used the Analysis of the modified variables: Researchers employed modified analysis to discern whether the effect of enrichment program interventions for gifted students on the development of their cognitive dimensions differs depending on the type of participants (males, females, males and females together), and the academic stage (primary, intermediate, secondary). This is evident from Table  5 ,

It is apparent from Table  5 that there are statistically significant differences in the average effect size according to the type of participants (males, females, males and females together), in favor of both males and females together (P < 0.001). Additionally, statistically significant differences were found according to the academic level (primary, intermediate, secondary) in favor of the secondary level (P = 0.001).

5 Discussion

The primary aim of the present study was to conduct a rigorous analysis with the intent of elucidating the impacts of enrichment program interventions on the development of prospective problem-solving skills and the cognitive dimensions within a cohort of gifted students. This was achieved through the employment of both correlational and quasi-experimental research designs, with the purpose of unveiling the moderating factors intrinsic to these effects. For this purpose, a total of ten research inquiries were subjected to scrutiny, encompassing three correlational studies and seven quasi-experimental investigations conducted from 2010 to 2023. The ensuing discourse will center upon the findings pertaining to each of the study's research questions, which are as follows:

This section starts with the first question enquiring about the effect size average of the impact of enrichment program interventions based on future problem-solving skills for gifted students in fostering their cognitive dimensions, according to correlational designs. The results, in response to this question, have determined that the common effect size, as per the random-effects model, attains a value of 0.531 with a standard error of 0.004 and 95% confidence intervals (0.317, 0.694). This effect size, for future problem-solving program interventions, resides within the realm of substantial effects, in accordance with what [ 17 ] has elucidated. Consequently, the influence of future problem-solving program interventions on the development of cognitive dimensions in gifted students, utilizing the correlational design, is indeed large. Researchers expound that future problem-solving programs are efficacious in the cultivation of cognitive dimensions among gifted students, guiding them towards success in both their personal and professional lives. It is noteworthy that education specialists must direct enrichment programs to meet the needs of gifted students in this field and design programs commensurate with the knowledge and skills of gifted students at various educational stages. Moreover, these programs must be oriented toward enhancing critical and creative thinking skills among gifted students in both academic and non-academic domains, while providing the requisite resources to accomplish these objectives. Interest in the development of future problem-solving programs for gifted students is steadily increasing, as problem-solving is deemed an exceedingly crucial skill in the modern age. Cognitive dimensions for problem-solving skills encompass critical and creative thinking, idea and problem analysis, theoretical and practical thinking, and the ability to make appropriate decisions [ 24 , 46 ]. Research suggests that future problem-solving programs contribute to the development of critical and creative thinking capabilities among gifted students. Indeed, [ 8 ] study demonstrated that enrichment programs for future problem-solving assist gifted students in developing their analytical and critical thinking skills, thereby enhancing their academic performance. Future problem-solving programs also aid in the development of theoretical and practical thinking. A study conducted in 2021 revealed that enrichment programs for future problem-solving help gifted students enhance their ability to analyze problems theoretically and practically, thereby enabling them to make sound decisions in diverse situations [ 54 ]

Furthermore, the current study's findings align with those conducted by [ 43 ], which showed that enrichment programs for future problem-solving facilitate gifted students in developing their ability to make appropriate decisions, thereby assisting them in achieving success in their personal and professional lives.

Then, we discuss the second question enquiring about the extent to the effect size average of the impact of enrichment program interventions targeting future problem-solving skills for gifted students vary in terms of their cognitive dimension development according to correlational designs, as a result of participant type (males, females, both) and educational level (elementary, middle, high school. To respond to this question, researchers used a modified analysis to discern whether the impact of future problem-solving intervention programs for gifted students on the cultivation of their cognitive dimension skills, as per correlational designs, indicated statistically significant differences in effect size attributed to the participant variables (males, females, males and females together), favoring the female participants, and the educational stage (elementary, middle, secondary), favoring the secondary stage. Researchers expound upon these findings by acknowledging the divergent aptitudes and requirements of gifted students across various educational stages. Indeed, students in the lower echelons may necessitate a greater emphasis on fundamental skills, while those in the higher echelons yearn for more substantial challenges. The nature of talent also varies among students participating in enrichment programs, with some demonstrating academic inclinations and others displaying artistic or socio-emotional proclivities. These differences significantly influence their responses to program interventions. The enrichment programs exhibit variances in terms of content, session duration, resource availability, and the expertise of supervisors, all of which contribute to disparities in the magnitude of the effect. Thus, disparities in the effect size of enrichment programs can be attributed to multiple variables related to the nature of the students, program content, and methodologies, as elucidated by experimental designs in this domain. Studies conducted in this domain [ 5 , 56 ] have demonstrated the pivotal role played by participant characteristics in determining the effect size of enrichment programs on the cognitive dimensions of gifted students. Results have shown statistically significant differences in the effect size of enrichment programs in favor of females. This might be attributed to gender disparities in educational interests, proclivities, and career aspirations, all of which influence the responses of gifted students to enrichment program interventions. Regarding the educational stage, studies [ 32 , 38 ] have indicated substantial variations in the effect size of enrichment programs across different educational stages. It has been revealed that the secondary stage yields superior results in the development of cognitive dimensions in gifted students compared to other stages. This can be attributed to variations in academic achievement levels and cognitive maturity among different educational stages, which impact the responses of gifted students to enrichment program interventions.

Enrichment programs for gifted students aim to provide educational opportunities that transcend standard curricula and intellectually challenge advanced learners. The effectiveness of such programs has been the subject of diverse research studies. Many studies have shown that participation in enrichment programs positively impacts the academic performance of gifted students. Research conducted by [ 29 ] found that students who participated in enrichment programs exhibited higher academic achievements, increased motivation, and enhanced critical thinking skills compared to their non-participating peers. Enrichment programs often offer opportunities for gifted students to explore their talents and develop advanced skills in specific fields. Research conducted by [ 39 ] elucidated that specialized enrichment programs focusing on specific areas such as mathematics, science, or the arts can accelerate learning and develop expertise.

The third question enquiring about the effect size average of the impact of enrichment program interventions based on future problem-solving skills for gifted students in fostering their cognitive dimensions, according to quasi-experimental designs, is then discussed. Hence, to address this question, an analysis of heterogeneity was employed to discern whether the observed variability in the research sample exhibited significant disparities beyond the anticipated variance due to observational error. The findings unequivocally elucidate the significant influence of enrichment programs for gifted students on the cultivation of their cognitive dimensions. These programs center their focus on stimulating critical and imaginative thinking in gifted students, who are the quintessence of cognitive evolution. They proffer challenges that nurture their loftier intellectual capacities and kindle unconventional problem-solving approaches and innovative ideation, thereby augmenting their cognitive capital [ 26 , 44 ]. Furthermore, these educational initiatives encompass projects and experiential learning activities, affording students the opportunity to construct knowledge through practical application. The enrichment programs hone gifted students' acquisition of advanced cognitive skills, encompassing critical thinking, problem resolution, and decision-making, thereby impacting the evolution of their cognitive dimensions [ 40 , 41 ]. Researchers elucidate that enrichment programs for gifted students wield a formidable influence on the augmentation of their cognitive dimensions. These programs are geared toward nurturing critical and creative thinking, which constitute the bedrock of cognitive development. They instill challenges designed to foster higher mental faculties, stimulating students to employ alternative methods in problem-solving and conceiving fresh ideas, thereby amplifying their cognitive endowment.

These programs hinge upon skills-based learning, affording gifted students opportunities to construct knowledge through experiential acquisition. They train students in the acquisition of elevated cognitive skills such as critical thinking and problem resolution, which significantly contribute to the enhancement of their cognitive dimensions. For these reasons, a multitude of studies have demonstrated the efficacy of enrichment programs in advancing the cognitive dimensions of gifted students.

The study's results concur with several extant research endeavors, much like the study conducted by [ 30 , 34 ], which evinced that the enrichment training program substantially facilitated the acquisition of critical thinking and problem-solving skills among gifted students. A study by [ 34 ] revealed a marked increase in the levels of critical and creative thinking among gifted students. The findings of a study by [ 31 ] demonstrated that enrichment programs significantly contributed to the enhancement of cognitive thinking skills, such as critical thinking and problem-solving, among gifted students.

Finally, this result related to question four, enquiring of to what extent the average magnitude of the impact of enrichment program interventions targeting future problem-solving skills for gifted students vary in terms of their cognitive dimension development according to quasi-experimental designs, as a result of participant type (males, females, both) and educational stage (elementary, middle, high school is discussed. To respond to this question, researchers undertook an elucidation of results, which unveiled statistically significant discrepancies in the mean effect size upon participant type (males, females, males and females together), favoring both males and females jointly. Furthermore, statistically meaningful distinctions about the educational level (elementary, middle, secondary) were unearthed, favoring the secondary level.

The findings in these studies revealed statistically significant disparities in the mean magnitude of the impact based on participant type and educational level. Concerning participant type, studies discovered disparities in the impact size of enrichment programs in favor of both males and females jointly, indicating that enrichment programs can be beneficial to both genders alike. Researchers expound this by suggesting that gifted individuals in the realm of sciences, such as critical and creative thinking, foster within themselves the zeal and enthusiasm to further their learning in this domain. The enrichment program proffers a diverse array of educational enriching activities, thus aiding in honing the students' skills in various scientific fields. The selection of students partaking in the enrichment program is contingent upon their distinguished prowess in the sciences, signifying their aptitude to assimilate and apply advanced scientific concepts more effectively. Regarding educational level, studies [ 14 , 22 ] found disparities in the impact size of enrichment programs in favor of the secondary level, implying that enrichment programs may be more efficacious in nurturing the cognitive abilities of gifted students in subsequent educational stages. This may be attributable to variations in mental and educational maturity levels and interests across educational stages.

This can be expounded upon by positing that gifted students possess greater experience in various academic subjects and exhibit higher levels of mental and intellectual maturity, rendering them more adept at comprehending and applying complex concepts and skills offered in enrichment programs.

Additionally, the educational interests of gifted students evolve across educational stages, as they become more specialized in specific fields and develop particular skills. Hence, enrichment programs that concentrate on these fields and skills may be more effective in enhancing their intellectual capacities [ 36 ]. These findings align with the study conducted by [ 23 ] to evaluate the effectiveness of the enrichment program employed by high school students in advancing their athletic intelligence and sports thinking. The results demonstrated significant enhancements in the levels of athletic intelligence and sports thinking among students who participated in the enrichment program. They also concur with a study by [ 8 ] assessing the efficacy of the enrichment program utilized by elementary and middle school students in improving their scientific skills. The study aimed to evaluate the effectiveness of the scientific enrichment program in enhancing the levels of scientific, intellectual, and creative thinking among gifted students in elementary and middle schools. The results of the enrichment program were assessed using scientific intelligence and scientific and creative thinking assessments, and the results of students who participated in the enrichment program were compared with those of a group of students who did not participate. The results indicated that the enrichment program achieved positive results in improving the levels of scientific intelligence and scientific and creative thinking in students.

6 Conclusion

In this study, the researchers analyzed the outcomes of previous research published between the years 2010 and 2023. These works delved into the future problem-solving skills within the domain of nurturing the gifted. This analysis was conducted via the meta-analysis approach, which hinges on the examination of results from prior studies, coupled with quantitative evaluation through various statistical procedures. These include impact assessment, magnitude assessment, and control of potential publication bias. After thorough examination of databases and journals, as many as 288 studies relevant to the study's title and objectives were identified. Studies that did not align with the prescribed study criteria were excluded, resulting in a reduction of the studies to ten. The study primarily focused on ascertaining the effectiveness of interventions pertaining to future problem-solving programs in developing the cognitive dimensions of gifted students. This evaluation was conducted according to correlational and quasi-experimental designs. Furthermore, the investigation sought to determine the average variance in the impact size of these future problem-solving interventions on the development of cognitive dimensions among gifted students, categorized by participant gender (male, female, and mixed) and academic stage (primary, middle, and secondary). The study's findings in this regard indicated that the effectiveness of future problem-solving program interventions, under both correlational and quasi-experimental research designs, demonstrated a high degree of effectiveness. As for the examination of the average variance in the impact size of future problem-solving program interventions on the development of cognitive dimensions, considering the participant type and academic stage, the results displayed disparities based on the research designs. Studies adopting correlational research designs pointed to differences based on academic stage, favoring the secondary stage, and gender-based differences favoring females concerning participant type. On the other hand, studies employing quasi-experimental research designs showed variations based on academic stage consistent with the findings from correlational research, favoring the secondary stage. However, concerning the participant type, there were statistically significant differences favoring both males and females.

7 Recommendations

In light of the findings derived, the researchers proffer the following suggestions:

Studies of this nature, as pursued in the current research, are exceedingly scarce in the realm of gifted education, and their outcomes cannot be universally extrapolated. Hence, an imperative requirement manifests for the execution of further investigations to validate result precision.

Those entrusted with the formulation of enrichment programs for the gifted ought to be rooted in the cultivation of future problem-solving competencies, while taking into account a multitude of factors, notably their alignment with the age bracket, gender, and societal cultural context. It has been observed that differential impact surfaces across the more advanced developmental stages.

8 Future proposed studies

Future studies suggest that meta-analysis studies are needed to reveal the effect of future problem-solving skills on other variables (psychological, social, and emotional) through experimental and correlational designs. It is also recommended that more meta-analysis studies on enrichment programs based on future problem-solving on studies published in peer-reviewed journals to clarify the effect of culture and form a clear picture of the results.

9 Limitations of the study

Like any other study, this research has some limitations. For example, the study targeted only the previous literature available in Arabic and English, ignoring her studies conducted in different languages, which may have some biases. It is to be noted that the studies related to males were very few compared to those about females or both sexes. The study included only those with open sources due to the difficulties in accessing non-open source articles. Furthermore, while searching, about 32 reports were not retrieved, which might have some influence on the study findings.

Data availability

The data used to support the findings of this study are available upon request. However, please note that the data for this article were generated as part of a project funded by King Faisal University. Due to the nature of the funding and to protect intellectual property rights, the data cannot be shared without prior permission from King Faisal University.

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This work was supported by the Deanship of Scientific Research, Vice President for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. 241554].

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Contribution: The contributions of each author to the research paper are as follows: Khaled Elballah—Formal Analysis—Funding Acquisition Norah Alkhalifah—Investigation.—Research Methodology Asma Alomari—Conceptualization—Data Curation Amal Alghamdi—Project Administration—Resources—Software.

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Elballah, K., Alkhalifah, N., Alomari, A. et al. Enhancing cognitive dimensions in gifted students through future problem-solving enrichment programs. Discov Sustain 5 , 248 (2024). https://doi.org/10.1007/s43621-024-00470-5

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DOI : https://doi.org/10.1007/s43621-024-00470-5

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Student-centered active learning improves performance in solving higher-level cognitive questions in health sciences education.

Simple Summary

1. introduction, 2. materials and methods, 2.1. study design, 2.2. theoretical lectures, 2.3. informative sessions, 2.4. student surveys, 2.5. learning outcomes assessment, 3.1. learning outcomes assessment, 3.2. survey conducted during the information session on active learning, 3.2.1. academic year 2022/2023.

• 27% of the students had experience with problem-based learning.
• 72% had experienced collaborative learning.
• 27% were familiar with flipped learning.

3.2.2. Academic Year 2023/2024

• Almost all students indicated they had no prior experience with any form of active learning.
• 79% had experience with collaborative learning.
• 56% knew what flipped learning was.
• 10% of the students chose option (a): “Expository teaching, where the teacher tells me everything I need to know”.
• 89% of students chose option (b): “Active teaching, where I learn to think about and use the content I am learning under the guidance of the teacher”.
• 1% of students chose option (c): “I don’t care, I can always be a GoogleVet”.

3.3. Anonymous Survey Conducted at the End of the Thematic Block

3.4. anonymous survey conducted at the end of the experience, 3.5. students attending to discussion session, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Martín-Alguacil, N.; Avedillo, L. Student-Centered Active Learning Improves Performance in Solving Higher-Level Cognitive Questions in Health Sciences Education. Int. Med. Educ. 2024 , 3 , 346-362. https://doi.org/10.3390/ime3030026

Martín-Alguacil N, Avedillo L. Student-Centered Active Learning Improves Performance in Solving Higher-Level Cognitive Questions in Health Sciences Education. International Medical Education . 2024; 3(3):346-362. https://doi.org/10.3390/ime3030026

Martín-Alguacil, Nieves, and Luis Avedillo. 2024. "Student-Centered Active Learning Improves Performance in Solving Higher-Level Cognitive Questions in Health Sciences Education" International Medical Education 3, no. 3: 346-362. https://doi.org/10.3390/ime3030026

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Computer Science > Computer Vision and Pattern Recognition

Title: columbus: evaluating cognitive lateral understanding through multiple-choice rebuses.

Abstract: While visual question-answering (VQA) benchmarks have catalyzed the development of reasoning techniques, they have focused on vertical thinking. Effective problem-solving also necessitates lateral thinking, which remains understudied in AI and has not been used to test visual perception systems. To bridge this gap, we formulate visual lateral thinking as a multiple-choice question-answering task and describe a three-step taxonomy-driven methodology for instantiating task examples. Then, we develop COLUMBUS, a synthetic benchmark that applies the task pipeline to create QA sets with text and icon rebus puzzles based on publicly available collections of compounds and common phrases. COLUMBUS comprises over 1,000 puzzles, each with four answer candidates. While the SotA vision-language models (VLMs) achieve decent performance, our evaluation demonstrates a substantial gap between humans and models. VLMs benefit from human-curated descriptions but struggle to self-generate such representations at the right level of abstraction.

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