research studies on academic achievement

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In This Article Expand or collapse the "in this article" section Academic Achievement

Introduction, general overviews.

• National and International Reports
• Measuring Academic Achievement
• Intelligence
• Personality
• Students’ Familial Background
• Other Variables Predicting Academic Achievement

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Academic Achievement by Ricarda Steinmayr , Anja Meißner , Anne F. Weidinger , Linda Wirthwein LAST REVIEWED: 30 July 2014 LAST MODIFIED: 30 July 2014 DOI: 10.1093/obo/9780199756810-0108

Academic achievement represents performance outcomes that indicate the extent to which a person has accomplished specific goals that were the focus of activities in instructional environments, specifically in school, college, and university. School systems mostly define cognitive goals that either apply across multiple subject areas (e.g., critical thinking) or include the acquisition of knowledge and understanding in a specific intellectual domain (e.g., numeracy, literacy, science, history). Therefore, academic achievement should be considered to be a multifaceted construct that comprises different domains of learning. Because the field of academic achievement is very wide-ranging and covers a broad variety of educational outcomes, the definition of academic achievement depends on the indicators used to measure it. Among the many criteria that indicate academic achievement, there are very general indicators such as procedural and declarative knowledge acquired in an educational system, more curricular-based criteria such as grades or performance on an educational achievement test, and cumulative indicators of academic achievement such as educational degrees and certificates. All criteria have in common that they represent intellectual endeavors and thus, more or less, mirror the intellectual capacity of a person. In developed societies, academic achievement plays an important role in every person’s life. Academic achievement as measured by the GPA (grade point average) or by standardized assessments designed for selection purpose such as the SAT (Scholastic Assessment Test) determines whether a student will have the opportunity to continue his or her education (e.g., to attend a university). Therefore, academic achievement defines whether one can take part in higher education, and based on the educational degrees one attains, influences one’s vocational career after education. Besides the relevance for an individual, academic achievement is of utmost importance for the wealth of a nation and its prosperity. The strong association between a society’s level of academic achievement and positive socioeconomic development is one reason for conducting international studies on academic achievement, such as PISA (Programme for International Student Assessment), administered by the OECD (Organisation for Economic Co-operation and Development). The results of these studies provide information about different indicators of a nation’s academic achievement; such information is used to analyze the strengths and weaknesses of a nation’s educational system and to guide educational policy decisions. Given the individual and societal importance of academic achievement, it is not surprising that academic achievement is the research focus of many scientists; for example, in psychology or educational disciplines. This article focuses on the explanation, determination, enhancement, and assessment of academic achievement as investigated by educational psychologists.

The exploration of academic achievement has led to numerous empirical studies and fundamental progress such as the development of the first intelligence test by Binet and Simon. Introductory textbooks such as Woolfolk 2007 provide theoretical and empirical insight into the determinants of academic achievement and its assessment. However, as academic achievement is a broad topic, several textbooks have focused mainly on selected aspects of academic achievement, such as enhancing academic achievement or specific predictors of academic achievement. A thorough, short, and informative overview of academic achievement is provided in Spinath 2012 . Spinath 2012 emphasizes the importance of academic achievement with regard to different perspectives (such as for individuals and societies, as well as psychological and educational research). Walberg 1986 is an early synthesis of existing research on the educational effects of the time but it still influences current research such as investigations of predictors of academic achievement in some of the large-scale academic achievement assessment studies (e.g., Programme for International Student Assessment, PISA). Walberg 1986 highlights the relevance of research syntheses (such as reviews and meta-analyses) as an initial point for the improvement of educational processes. A current work, Hattie 2009 , provides an overview of the empirical findings on academic achievement by distinguishing between individual, home, and scholastic determinants of academic achievement according to theoretical assumptions. However, Spinath 2012 points out that it is more appropriate to speak of “predictors” instead of determinants of academic achievement because the mostly cross-sectional nature of the underlying research does not allow causal conclusions to be drawn. Large-scale scholastic achievement assessments such as PISA (see OECD 2010 ) provide an overview of the current state of research on academic achievement, as these studies have investigated established predictors of academic achievement on an international level. Furthermore, these studies, for the first time, have enabled nations to compare their educational systems with other nations and to evaluate them on this basis. However, it should be mentioned critically that this approach may, to some degree, overestimate the practical significance of differences between the countries. Moreover, the studies have increased the amount of attention paid to the role of family background and the educational system in the development of individual performance. The quality of teaching, in particular, has been emphasized as a predictor of student achievement. Altogether, there are valuable cross-sectional studies investigating many predictors of academic achievement. A further focus in educational research has been placed on tertiary educational research. Richardson, et al. 2012 subsumes the individual correlates of university students’ performance.

Hattie, John A. C. 2009. Visible learning: A synthesis of over 800 meta-analyses relating to achievement . London: Routledge.

A quantitative synthesis of 815 meta-analyses covering English-speaking research on the achievement of school-aged students. According to Hattie, the influences of quality teaching represent the most powerful determinants of learning. Thereafter, Hattie published Visible Learning for Teachers (London and New York: Routledge, 2012) so that the results could be transferred to the classroom.

OECD. 2010. PISA 2009 key findings . Vols. 1–6.

These six volumes illustrate the results of the Programme for International Student Assessment (PISA) 2009—the most extensive international scholastic achievement assessment—regarding the competencies of fifteen-year-old students all over the world in reading, mathematics, and science. Furthermore, the presented results cover the effects of student learning behavior, social background, and scholastic resources. Unlimited online access.

Richardson, Michelle, Charles Abraham, and Rod Bond. 2012. Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin 138:353–387.

DOI: 10.1037/a0026838

A current and comprehensive review concerning the prediction of university students’ performance, illustrating self-efficacy to be the strongest correlate of tertiary grade point average (GPA). Cognitive constructs (high school GPA, American College Test), as well as further motivational factors (grade goal, academic self-efficacy) have medium effect sizes.

Spinath, Birgit. 2012. Academic achievement. In Encyclopedia of human behavior . 2d ed. Edited by Vilanayur S. Ramachandran, 1–8. San Diego, CA: Academic Press.

A current introduction to academic achievement, subsuming research on indicators and predictors of achievement as well as reasons for differences in education caused by gender and socioeconomic resources. The chapter provides further references on the topic.

Walberg, Herbert J. 1986. Syntheses of research on teaching. In Handbook of research on teaching . 3d ed. Edited by Merlin C. Wittrock, 214–229. New York: Macmillan.

A quantitative and qualitative aggregation of a variety of reviews and quantitative syntheses as an overview of early research on educational outcomes. Walberg found nine factors to be central to the determination of school learning.

Woolfolk, Anita. 2007. Educational psychology . 10th ed. Boston: Pearson.

Woolfolk represents a comprehensive basic work that is founded on an understandable and practical communication of knowledge. The perspectives of students as scholastic learners as well as teachers are the focus of attention. Suitable for undergraduate and graduate students. Currently presented in the 12th edition.

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Academic Achievement

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• Nicholas Bolt 3  

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Educational ; Scholastic ; School performance/achievement

Academic Achievement is the progress made towards the goal of acquiring educational skills, materials, and knowledge, usually spanning a variety of disciplines. It refers to achievement in academic settings rather than general acquisition of knowledge in non-academic settings.

Description

Unlike typical forms of achievement, academic achievement is usually viewed without a definitive endpoint. Rather, the concept is understood as a spectrum along which one can “achieve” certain skills and knowledge, always with the possibility of further developing those skills and increasing the depth, breadth, and specificity of knowledge.

Academic achievement revolves around the central goal of improving the educational knowledge of the students. Because of this goal, the measurement of achievement is often criticized for maintaining a focus on content knowledge rather than problem-solving or product-fashioning skills across...

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Nitko, A. J. (2001). Educational assessment of students (3rd ed.). Upper Saddle River, NJ: Merrill/Prentice Hall.

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Welsh, M., Parke, R. D., Widaman, K., & O’Neil, R. (2001). Linkages between children’s social and academic competence: A longitudinal analysis. Journal of School Psychology, 39 (6), 463–481.

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Bolt, N. (2011). Academic Achievement. In: Goldstein, S., Naglieri, J.A. (eds) Encyclopedia of Child Behavior and Development. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-79061-9_20

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Determinants of academic achievement among higher education student found in low resource setting, A systematic review

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of psychiatry, Dilla University, Dilla, Ethiopia, Faculty of Social Sciences, Lobachevsky State, University of Nizhny Novgorod, Nizhny Novgorod, Russia

Affiliation Department of Social Security and Humanitarian Technologies, Nizhny Novgorod State University, Nizhniy Novgorod, Russia

• Chalachew Kassaw, 
• Valeriia Demareva

Published: November 20, 2023

• https://doi.org/10.1371/journal.pone.0294585
• Reader Comments

Academic success is a measure of students’ ability to attain their educational objectives, often assessed through regular evaluations or examinations. To establish effective policies and programs that align with academic accomplishments, conducting comprehensive data analysis is pivotal. Hence, this systematic review aimed to synthesize the factors impeding the academic achievements of Ethiopian students in higher education.

A comprehensive review was conducted on studies involving Ethiopian university students from 2013 to 2022. The review encompassed 24 papers that were gathered from different databases like PubMed, Google Scholar, African Journals Online, Scopus, and Web of Science.

The findings of this research revealed that inadequate classroom environments, experiencing dysmenorrhea, and engaging in excessive social media usage were all linked to a decline in academic performance. Conversely, adopting healthy sleep habits, achieving high scores in entrance exams, and avoiding recent substance abuse were all factors positively influencing academic success. In addition, there was a positive correlation between academic excellence and being a health science college student and age range of 20 to 24 years old.

To enhance academic performance, it is crucial to address the negative factors identified, such as inadequate classroom environments, dysmenorrhea, and excessive social media usage, while promoting positive factors like healthy sleep habits, high scores in exams, and avoiding substance abuse. Additionally, being a health science college student and belonging to the age range of 20 to 24 were found to be associated with academic excellence.

Citation: Kassaw C, Demareva V (2023) Determinants of academic achievement among higher education student found in low resource setting, A systematic review. PLoS ONE 18(11): e0294585. https://doi.org/10.1371/journal.pone.0294585

Editor: Mukhtar Ansari, University of Hail, SAUDI ARABIA

Copyright: © 2023 Kassaw, Demareva. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: This article does not report data and the data availability policy is not applicable.

Funding: The authors received no specific funding for this work.

Competing interests: Declaration of Competing Interest: There are no apparent conflicts of interest with this publication.

Introduction

Academic success pertains to the extent of accomplishment exhibited by a student or institution in attaining educational objectives, regardless of whether they are immediate or long-range in nature [ 1 ]. Education is a formidable catalyst for transforming a nation’s societal harmony, economic prosperity, standard of living, and overall well-being [ 2 ]. Graduation rates evaluate the performance of an institution, while GPA (Grade Point Average) measures the achievements of individual students [ 3 ]. GPA (Grade Point Average) is calculated by dividing the sum of grade points by the total units [ 4 ]. The assessment of students’ knowledge and skills attained from each subject depends on the subject-area measurement level [ 5 ].

Higher education institutions play a vital role in creating an environment that promotes learning and supports the development of global competencies in various academic disciplines. This, in turn, allows learners to effectively navigate the ever-changing global landscape. Ultimately, such efforts enhance the overall quality of education and equip students to successfully overcome challenges [ 6 ]. Learning is a lifelong and challenging process that does not guarantee the attainment of knowledge, skills, or perspectives. It requires significant effort and time [ 7 ]. In order to succeed in school, students must exhibit initiative, self-control, effective time management, focused attention, inquisitiveness, and active engagement in the classroom [ 8 ]. Good academic performance offers numerous benefits, including improved living conditions, increased productivity, and better economic prospects for society. It also provides students with a positive self-image, confidence, good mental health, social skills, and a clear vision for their future [ 9 ]. Poor academic performance in students can potentially lead to a range of psychological problems, such as substance abuse, criminal behavior, promiscuity, and conflicts in relationships [ 10 ]. There were also encounters of difficulties with timely graduation due to retakes and grade changes, strained relationships with professors and support staff, as well as conflicts with college deans and students [ 11 ]. The government’s extensive educational efforts have failed to assist many students in achieving higher academic levels [ 12 ]. The number of students enrolling in Ethiopia’s higher education institutions is not comparable to the number of graduates because a significant portion of applicants are initially rejected, then withdraw, and ultimately get readmitted [ 13 ]. Challenging situations can often result in family struggles, dependence, lack of insurance, poverty, and insufficient access to healthcare coverage [ 14 ]. The effectiveness of teaching and learning tools, along with the students’ personality, goals, and teachers’ skills, all have an impact on academic progress. Studies have shown that the environment also plays a critical role in students’ performance in school [ 15 ]. Academic achievement is influenced by several factors, including finances, study habits, time management, health, and family connections, all of which are significant [ 16 ]. Poor academic performance has been found to be linked to several factors, including sporadic school attendance, low parental education, unstable family relationships, excessive use of social media, and spending excessive amounts of time engaging in conversation [ 17 ]. Research conducted by national universities has identified specific characteristics that are consistently associated with poor academic performance [ 18 ]. For instance, a study conducted by Bahir Dar University discovered that a student’s academic status is influenced by the education level of their parents and their tendency to frequent pubs and clubs [ 19 ]. However, the results of a study at Arba Minch University showed that a student’s past academic achievement largely predicts their present performance on campus [ 20 ]. An additional examination conducted at Wolayita Sodo University discovered a correlation between present drug usage and academic achievement [ 21 ]. Currently, there are 42 public institutions in the country, all of which strive arduously to improve the quality of education [ 22 ]. Assessing the academic performance of students is crucial for ensuring quality assurance in higher education institutions. However, analyzing national averages of academic predictors is an essential tool for developing academic policies and strategies that can enhance education quality on a broader scale. This review specifically aimed to identify the main predictors of academic achievement based on studies conducted among universities located in different regions of Ethiopia. The review found that participation in a supportive academic environment, acquiring essential information, maintaining a positive outlook, and possessing subject-specific abilities are crucial factors for student success. While numerous individual studies have been conducted in various parts of the country that have identified potential factors associated with academic achievement, decision-makers who are striving to improve academic standards in Ethiopian higher education institutions will find this comprehensive review particularly beneficial. Moreover, the review also identified areas of knowledge gaps that require further exploration in order to enhance academic quality throughout the country.

Study design and setting

A systematic review covering studies conducted in Ethiopian higher education institutions between 2013 and 2022 was conducted between January and February of 2023. As of 2023, Ethiopia will have 83 private institutions, 42 public universities, and 677 study options. Additionally, more than 150,000 adults graduate annually in the country. The universities offer training for students pursuing undergraduate, graduate, and doctoral degrees [ 23 ]. We have checked the Prospero database ( http://www.library.ucsf.edu/ ) to determine if there are any published or ongoing projects related to the topic, in order to avoid any duplication. The findings revealed that there are no ongoing or published articles in the area of this topic. The current systematic review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria ( S1 File ) [ 24 ].

Searching strategy and source of information

An extensive literature search was conducted using international databases, including PubMed, Scopus, Google Scholar, African Journals Online, and Web of Science, to retrieve relevant articles. Search terms were formulated following the Population, Intervention, Comparison, and Outcomes (PICO) framework and applied to the online databases. Medical Subject Headings (MeSH) terms and key terms were developed using various Boolean operators, such as "AND" and "OR." The following search terms were used: “Academic Achievement”, OR “Academic Performance” OR “Average Cumulative Grade Point”, OR “Performance Indicators” AND Psychological Determinants”, “Biological Determinants”, “Social Determinants”, “Higher Education”, “Competency Measures”, AND “Teaching-learning styles Predictors” AND “Ethiopia” ( S2 File ).

Eligibility criteria

The authors performed an unbiased eligibility examination based on the provided criteria. Issues were resolved through mutual agreement and the involvement of other authors. This systematic review analyzed articles written in English, published between 2013–2022 and that investigated predictors of academic achievement among higher education students. Only studies with cross-sectional designs, defined outcome variables, and covariates were included. This research aimed to identify factors that contribute to academic success among college students. Studies that did not use basic statistical analysis (Prevalence, Mean, ANOVA, T-test, adjusted odds ratio and Crude odd ratio) to establish the connection between academic performance and its influencing factors were excluded from the review.

Operational definitions

Outcome measurement (academic achievement)..

Grade Point Average (GPA): Grade point average (GPA) is a value calculated by multiplying the unit value for each course by the grade point total and then dividing the sum by the total number of units.

A checklist: An assessment tool lists the specific criteria for skills, behaviors, or attitudes that participants must demonstrate to show that they have successfully learned from training.

Writing assessment: It refers to a field of study that contains theories and practices that guide the evaluation of a writer’s performance or potential through writing tasks.

Interview assessment: An interview based test used to evaluate a student’s suitability for the particular subject they wish to pursue in a specific department.

A skills gap analysis: It is a tool used to assess the gap between a student’s current capabilities and the requirements of a particular profession, both current and future.

Determinant factors of the outcome measurement.

Psychological factors: The internal influences shape our thoughts, feelings, and behaviors.

It includes mental pain, sleep quality, self-esteem, prosocial behavior, anxiety, depression, and suicidality.

Biological factors: These are the physical and chemical influences on our bodies and minds.

It includes gender, age, and hormonal issues (dysmenorrhea). Facility-related factors: This physical and environmental conditions support student learning. It includes availability of adequate seating and studying spaces, lighting, technology, equipment and supplies, sleeping accommodations, dining halls, sports fields, green spaces and other outdoor areas.

Life style factors: These are the choices and behaviors that people make that can affect their health and well-being. It includes excessive social media usage, premarital sex, and sexual abstinence.

Study selection and data extraction.

The researchers used the reference management software Mendeley, Desktop and Endnote version 25 to remove duplicate articles from the search results. Three independent reviewers then screened the titles and abstracts of the remaining articles to determine eligibility for the review. Any disagreements between the reviewers were resolved based on pre-established criteria. Two independent reviewers then extracted data from the eligible articles using a standardized data extraction form created in Microsoft Excel. Any discrepancies during data extraction were resolved through discussion. The data that was extracted included the name of the first author, study area and region, study month and year, study design, year of publication, study population, sample size, response rate, and level of good knowledge, positive attitude, and poor practice.

Quality assessment

To assess the quality of each study included in this systematic review, we used the modified Newcastle Ottawa Quality Assessment Scale (NOS) for cross-sectional studies [ 25 ]. Both authors (Chalachew Kassaw and Valeria Demareva) independently assessed the quality of each study, considering the following factors: methodological quality, sample selection, sample size, comparability of the study groups, outcome assessment, and statistical analysis. In the case of disagreement between authors, other reviewers were involved to resolve the issue. All studies included in this systematic review were cross-sectional, quantitative, or qualitative studies ( S3 File ).

Study search and selection

This study conducted a systematic review of academic achievement and its related factors by limiting the search to full-text articles in English published between 2013 and 2022 in the following databases: PubMed, Scopus, Google Scholar, African Journals Online, and Web of Science. A total of 67 primary papers were found, and 19 and 20 publications were discarded as duplicates and unrelated to the study, respectively, after title and abstract screening. Of the remaining 28 papers, four were excluded due to inadequate evidence of the relationship between academic achievement and its factors. Finally, 24 papers that met all inclusion requirements were selected for the systematic review. The rigorous methodology used in this study highlights the importance of selecting relevant papers to establish robust findings that can support subsequent research on academic achievement and its factors ( Fig 1 ).

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https://doi.org/10.1371/journal.pone.0294585.g001

Most systematic reviews of academic achievement and its factors among college students in Ethiopia focus on average grade point and performance evaluation indicators, adapting these metrics to their research goals and regional contexts [ 26 – 32 ] However, high-quality research on the topic in Ethiopia is scarce. This study analyzed eligible peer-reviewed papers from various Ethiopian colleges published between 2013 and 2022. Most of these studies were cross-sectional and included samples of both men and women from institutions. However, two studies used a cross-sectional, qualitative design [ 33 , 34 ]. Most of the studies we reviewed [ 26 – 32 ] examined sociodemographic factors such as age, gender differences, and monthly pocket money as potential contributors to academic achievement. However, a small proportion of studies, specifically those that examined the relationship between menstruation and academic success, included interviews with women [ 35 , 36 ]. This study review included participants from all part of the nation, aged 18–35 years with an average of 21.2 years. It found that factors such as biological, psychological, social, student-teacher interaction and lifestyle characteristics are predictive of academic achievement (Tables 1 – 4 ).

https://doi.org/10.1371/journal.pone.0294585.t001

https://doi.org/10.1371/journal.pone.0294585.t002

https://doi.org/10.1371/journal.pone.0294585.t003

https://doi.org/10.1371/journal.pone.0294585.t004

Psychological predictors of academic achievement

According this study review result, sleep quality, mental distress, suicidal ideation, perceived stress, low self-esteem, depression, pro-social behavior and test anxiety were identified factors associated with academic achievement ( Table 1 ).

Biological predictors of academic achievement

Gender difference (male), age difference (20–24 years old), psychoactive substance use and menstrual related factors (dysmenorrhea and long menses period) were associated with academic achievement ( Table 2 ).

Facility and educational environment predictors of academic achievement

This study review revealed that Dormitory crowdedness, inadequate anatomy-teaching model, low internet access, Past English achievement, Entrance exam result, students’ perception of teachers, students’ academic self -perception and students’ social self-perception were associated with academic achievement ( Table 3 ).

Life style predictors of academic achievement

Student’s life style factors such as pre-marital sex, sexual abstinence and excessive social media (Facebook, What up and telegram) use were associated with academic achievement ( Table 4 ).

Summary of predictors of academic achievement

Several studies have found a significant negative correlation between academic achievement and factors. This include facility related factors such as large class sizes, insufficient internet access, poor classroom amenities, and teaching methods. Lifestyle style related factors such as excessive social media usage, premarital sex, and sexual abstinence have also been shown to have an impact on academic achievement. Psychlogical factors such as perceived stress, a lack of social support, and low self-esteem have also been found to influence academic success. Finally, Biological factors such as gender, age above 24, and hormonal issues, especially dysmenorrhea, are other factors that have been shown to have a significant impact on academic performance ( Fig 2 ).

https://doi.org/10.1371/journal.pone.0294585.g002

This systematic review explored the factors affecting academic success in Ethiopian higher education. Both modifiable and non-modifiable characteristics were identified as predictors of academic achievement.

Socio-economic factors

This study review found that individuals with low socioeconomic status, specifically low monthly income and inadequate social support, were more likely to experience poor academic performance. This review result is similar with a systematic review done in Belgium [ 50 ], Pakistan [ 51 ], and Netherlands [ 52 ]. Financial constraints can prevent students from accessing basic educational tools, such as pencils, paper, laptops, and notebooks, which are necessary to attend classes efficiently and achieve good academic results. Students with strong social support are highly motivated to succeed in their studies, cope with challenges, manage stress and anxiety, and have opportunities to collaborate with others, discuss ideas, and get feedback on their work. Providing daily necessities such as financial and emotional support is essential for students’ physical and mental well-being.

Biological factors

The study also found that biological factors, such as gender, age, and menstrual cycle-related hormone changes, are associated with academic success. These findings are consistent with research conducted in low- and middle-income countries [ 53 ] and Saudi Arabia [ 54 ] and China [ 55 ]. Advanced age may cause changes in all parts of the body, including the brain. Certain parts of the brain shrink, especially those that are important for learning and other complex mental processes [ 56 ]. Neuronal transmission may become less efficient in some areas of the brain as people age, which can lead to a decline in working memory and make tasks like making decisions and resolving problems more challenging [ 57 ]. Students with dysmenorrhea may miss classes, assignments, and tests, be reluctant to participate in class discussions or activities, experience pain and discomfort during class and study, and find it difficult to focus and concentrate, all of which can lead to lower academic achievement.

Estrogen increases the production of acetylcholine, a brain enzyme essential for memory, and strengthens neuronal connections in the hippocampus, a region of the brain critical for language recall. Estradiol, a hormone prevalent in women, is particularly important for word memory, focus, and rapid information processing [ 58 , 59 ].

Psychological factors

This study review found that mental and psychological conditions such as melancholy, anxiety, suicidal thoughts, low self-esteem, perceived stress, prosocial behavior, and sleep disorders are important indicators of academic achievement in higher education. This finding was consistent with a research conducted in Italy [ 60 ], Australia [ 61 ], Nepal [ 62 ] and China [ 63 ]. Mental health issues can negatively influence students’ academic success by reducing their energy, focus, motivation, cognitive abilities, and optimism. Depressed or anxious students may find it difficult to socialize and participate in class, which can lead to a decline in their academic performance. Students struggling with mental health concerns may also become less engaged and proactive in their studies [ 64 , 65 ].

Life style factors

The systematic review found that premarital sex, social media use, and sexual abstinence could affect a person’s way of life. The same conclusion was reached in a Latin American study [ 66 ] and China [ 67 ]. Students who engage in premarital sex may be more likely to experience academic failure for a number of reasons. They may spend more time with their partners, miss more classes, and get distracted. They may also feel guilty, low self-esteem, and susceptible to physical illnesses. All of these factors can contribute to academic problems [ 68 ]. A major drawback of technology is that social media use can distract students from their academic work. When students are bombarded with both educational and entertainment messages, it can be difficult for them to concentrate on their lectures. Additionally, students may prioritize online chatting and building relationships on social media over reading books in their free time, which can further harm their academic performance [ 69 , 70 ].

This study also found that certain facility-related factors, such as crowded dorm quarters, large class sizes, inadequate classroom amenities, and restricted internet access, are associated with academic achievement. This result was supported with a study done United Kingdom [ 71 ], Malaysia [ 72 ] and Korea [ 73 ]. This may be explained by inadequate school infrastructure, which can distract, tire, and disengage students, making it difficult for them to learn effectively. Examples of poor school facilities include loud noises, crowding, poor lighting, and difficulty accessing instructional materials [ 74 ].

This review found that the field of study, a good student-teacher relationship, the absence of breaks, and the performance of previous students are all academically linked criteria, consistent with reviews and studies conducted in the United Kingdom [ 75 ], Unites States of America [ 76 ], Nepal [ 77 ] and China [ 78 ]. Students are more likely to study when they feel positive about their learning environment. This is because they are more motivated to learn when they feel a sense of belonging, competence, and autonomy in their academic setting [ 79 ]. Factors in your classroom environment can influence student motivation. Motivated students put more effort into learning activities, such as paying attention, overcoming challenges, interacting with others, forming friendships, and managing their emotions (e.g., sadness and anxiety) [ 80 ].

Strengths of the study review

The review searched five databases to retrieve relevant articles.

The review strictly followed PRISMA flow charts.

More than one assessor evaluated the quality of the studies.

The review used the appraisal process developed by the Joanna Briggs Institute (JBI).

The review included studies from all parts of the country, ensuring good representativeness.

Limitations of the study review

The measurements for academic achievement and operational definitions may have differed between the primary studies.

This systematic review analyzed the predictors of academic achievement in Ethiopian higher education students, as identified in primary studies conducted over the past 10 years. The review identified many factors that affect academic achievement, including controllable factors such as facility-related variables, emotional factors, and lifestyle factors. These include large class sizes, poor internet connections, inadequate classroom facilities, poor teaching strategies, perceived stress, lack of social support, and substance use.

Recommendation

Based on the findings of this systematic review, it is recommended that universities and colleges in Ethiopia take steps to improve facility-related resources, provide support for student emotional and mental well-being, educate students about healthy lifestyle choices, and develop and implement interventions to address specific predictors of academic achievement.

Improving facility-related resources includes reducing class sizes, improving internet access, and providing adequate classroom facilities and teaching materials. This can help to create a more conducive learning environment for students and support their academic success.

Providing support for student emotional and mental well-being can be done by offering counseling services, creating a supportive campus environment, and raising awareness of the importance of mental health. This can help to reduce stress and anxiety among students, which can improve their academic performance. Educating students about healthy lifestyle choices can be done through workshops, seminars, and other educational programs. This can help students to make informed decisions about their health and well-being, which can indirectly lead to improved academic achievement. Developing and implementing interventions to address specific predictors of academic achievement can involve a variety of strategies. For example, interventions could be designed to reduce stress, improve social support, and prevent substance use. These interventions can be tailored to the specific needs of the student population and can be delivered in a variety of settings, such as classrooms, residence halls, and student health centers. By taking these steps, universities and colleges in Ethiopia can help to improve the academic achievement of their students and create a supportive and inclusive learning environment.

Supporting information

S1 file. preferred reporting items for systematic reviews and meta-analyses (prisma) guideline..

https://doi.org/10.1371/journal.pone.0294585.s001

S2 File. Search strategy.

https://doi.org/10.1371/journal.pone.0294585.s002

S3 File. Newcastle-Ottawa Quality assessment scale.

https://doi.org/10.1371/journal.pone.0294585.s003

S4 File. Microsoft excel document.

https://doi.org/10.1371/journal.pone.0294585.s004

Acknowledgments

We would like to thank all authors of the studies included in this systematic review.

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• Published: 27 September 2024

Inhibitory control and academic achievement – a study of the relationship between Stroop Effect and university students’ academic performance

• Martin Dvorak 1  

BMC Psychology volume  12 , Article number:  498 ( 2024 ) Cite this article

Metrics details

While previous research has identified executive functions as predictors of academic performance in school children, similar studies conducted among adults show mixed results. One of the reasons given for executive functions having a limited effect on academic achievements in adulthood is that they are usually fully developed by that time. Since these executive functions are at their peak at that age, the individual differences in these as well as their influence on academic performance in adults are harder to trace. The paper describes a study conducted among 107 university students the goal of which was to find out whether there is any relationship between the adult students’ inhibitory control values measured with the Stroop Test and their academic achievements. Although the results indicate a weak correlation between the Stroop Effect and the students’ academic performance of low statistical significance, which seems to confirm the outcomes of the previous studies focusing on adults, the study reveals an unexpected statistically significant correlation between the students’ grade averages and the number of their incorrect color identifications. This phenomenon appears to be worth pursuing in future research since it suggests the existence of another, relatively quickly measurable, variable possibly reflecting other predictors of academic performance in adults such as a degree of their manifested conscientiousness, their ability to concentrate on an assigned, relatively short, one-off task and their attitude to fulfilling this task. The Stroop Test, despite not being originally designed for this purpose, might thus be used as a simple tool suitable for providing information about these variables via the subject’s number of color identification errors. Such information can subsequently inform the activities that educators may include in their curricula to foster conscientiousness and concentration in the students lacking these.

Peer Review reports

Introduction

As documented by previous research, academic performance as the “level of knowledge demonstrated in an area or subject compared to the norm for the particular age and level of education” [ 46 ] has been affected by a myriad of factors. These are socioeconomic [ 66 ], student-related (e.g. students’ self-control and class attendance) [ 25 , 29 ], or psychosocial [ 60 ]. Another factor documented as affecting academic performance is a complex of executive functions which appear to play a significant role in language development as well as the processing and organization of received information [ 57 ]. The processing of received information is done either through automatic attention or controlled attention. In the case of the former, the attention responses direct attention automatically to a target regardless of concurrent inputs or memory load. In the case of the latter, an active attention of the subject is required, which also makes the information processing limited in terms of processing capacity [ 63 ].

Executive functions encompass cognitive skills related to attention control, i.e. the process by which attention is selectively directed to specific aspects of a representation, particularly in misleading situations [ 11 ]. One of the attention control mechanisms can be switching attention between tasks where, in the case of a card-sort test, for instance, the subject must switch between different rules by which they sort cards (e.g. first by their shape and then by their color). Another mechanism is the inhibition of attention when it comes to the stimuli that need to be ignored. This inhibition is activated in, for instance, multilinguals when they need to suppress their temptation to use one (or more) of their languages not needed or inappropriate for a given situation [ 11 , 13 , 77 , etc.]. Other researchers [ 2 , 53 , etc.] work with the terms of inhibition (the ability to suppress dominant responses, a term synonymous to the attention inhibition mentioned above), shifting (the ability to switch over between tasks, a term synonymous to switching attention mentioned above) and monitoring (the ability to update information in the working memory). The working memory as a function that enables individuals to temporarily remember information while competitively processing information [ 54 ] has been mentioned as a factor influencing school performance even more than intelligence with the latter predicting a wide range of indicators of academic success [ 48 , 52 ].

Effect of executive functions on academic performance

Multiple studies emphasize the fact that educational research should pay more attention to executive functions since these represent essential ingredients for successful academic functioning [ 75 ] and since they also appear to be connected with school dysfunction as deficits in them have been associated with disabilities in mathematics and reading [ 51 , 70 ]. According to Pascual [ 57 ], who also mentions cognitive flexibility, i.e. the ability to temporarily manipulate information, and planning, the executive functions represent “distinct, but related, higher-order neurocognitive processes that control thought and behaviors aimed at achieving an objective goal” (p. 2). The existence of relationship between executive functions and academic achievement is also supported by other studies most of which investigate this relationship in children of pre-school or early-school age (e.g. [ 4 , 9 , 19 , 28 , 76 , etc.]) or those that study it in the context of learning disabilities [ 3 , 37 , 49 , 64 ].

Some studies also stress the fact that the positive contribution of executive functions to academic performance is domain-dependent, i.e. that certain executive functions contribute to gaining certain knowledge or skill more than others. Thus, inhibition, for instance, appears to be beneficial when it comes to mathematics and science [ 57 ]. Similarly, Gerst [ 38 ] found a direct relationship between inhibition and the ability to conduct mathematical calculations in children aged 10–11.

As there seems to be a variation in the way in which younger and older children solve calculations due to the age-related shift from the procedural-based processing in arithmetic tasks to more memory-based [ 72 , 7 , 16 , etc.] it is also different types of interference that appear to disrupt children at different ages. In a dual-task study McKenzie et al. [ 50 ], for instance, found out that the mathematical processing of 6-year-old children was disrupted only by a visuo-spatial passive interference task whereas in the 8-year-old ones it was disrupted by both a visuo-spatial and a phonological interference task. In this respect, the type of information processing deployed in problem solving appears to determine the type of irrelevant stimuli that need to be suppressed through inhibition for the students to complete an arithmetic task efficiently.

The executive function of inhibition is usually defined as the ability to suppress dominant but irrelevant responses and prioritize important information instead. This way “it moderates behavior, suppresses impulsive reactions to a stimulus, and enables an appropriate and thoughtful response” [ 57 ]. Cognitive inhibition is thus responsible for planning, analyzing and choosing the most appropriate response.

Negative effects of a low degree of inhibitory control on academic performance

The relationship between poor academic performance and poor performance in tasks requiring the inhibition of irrelevant information has been pointed out by multiple studies. Espy et al. [ 33 ], investigating how working memory and inhibitory control affect arithmetic competency, identified differences in the ability to inhibit irrelevant stimuli as a factor responsible for unique variance in mathematical skills. In mathematics, inhibitory control is used to inhibit information that should not be maintained in working memory for upcoming responding [ 27 ]. Similarly, Espy et al. point out that to flexibly shift responding in the face of conflicting rules requires maintaining the rule in mind and inhibiting prepotent, previous responses [ 33 ]. Passolunghi & Lanfranchi [ 55 ] mention inhibition as a factor influencing performance at the numerical competence test.

The importance of the role that inhibition plays in reading and listening comprehension has been pointed out by studies focusing on children. Passolunghi et al. [ 56 ], for instance, stress that groups of poor problem solvers tend to perform poorly in a working memory test requiring inhibition of irrelevant information and that this condition appears to be related to poor recall of critical information and greater recall of to-be-inhibited information. In addition, the process of reading often involves exposure to visual distractions such as images, graphs, etc. present in the very text as well as external physical distractors in the environment in which the reading takes place. In such situations, the inhibitory control helps the reader to stay focused on the written content. Similarly, De Beni et al. [ 26 ], showed that the “poor comprehenders” had a significantly lower performance in the listening span test associated with a higher number of intrusions. These intrusions can be background noise or competing sounds that need to be ignored for the listener to focus on and understand what a speaker is saying. In addition, both reading and listening often involve interpretation of figurative language, where the inhibition of the literal, irrelevant information enables the reader or listener to grasp the relevant meaning [ 39 ].

Inhibitory control as a facilitator of learning

The positive correlation between a degree of inhibitory control and academic achievement has been documented by other studies as well. Duckworth et al. [ 29 ], for instance, stress behavioral inhibition (self-control) as affecting academic performance. St Clair-Thompson & Gathercole [ 62 ] identify inhibition as a factor associated with achievement in English, mathematics, and science in 11- and 12-year-old children while Blair & Razza [ 14 ] point out that the inhibitory control correlated with both early math and reading ability in their study conducted among 3- to 5-year-old children. Privitera et al. [ 59 ] give a reason for why the improved inhibitory control leads to greater academic performance; the students with improved inhibitory control can focus on tasks both within and outside of the classroom better, ignoring the ever-growing number of distractions present in their environments. The authors also claim that this improved focus may result in superior academic performance. Irvan & Tsapali [ 44 ] point out the positive effect of improved inhibitory control on academic performance stating that the inhibition as an executive function appears particularly crucial for young children growing up and learning as they are exposed to constant distractions vying for their attention. Blair & Razza [ 14 ] also suggest that curricula designed to improve self-regulation skills and enhance early academic abilities may be most effective in helping children succeed in school.

Age-dependent effect of executive functions on academic performance

On the other hand, some sources conclude that the relationship between executive functions, with inhibitory control representing one of them, and academic performance appears to depend on age. Bryce et al. [ 15 ] focused on the relationship between executive functions and metacognitive skills, which they have identified as most significant predictors of educational achievements in their study groups of 5- and 7-year-old children. Their results indicate that executive functions appear to be more related to metacognitive skills in 5-year-olds than in 7-year-olds. In the study conducted among subjects aged 5–17, Best et al. [ 10 ] analyzed a varying correlation between executive functions and academic achievement in relation to age concluding that the correlation is strongest at the ages of 6, 8–9 and subsequently appears to be of somewhat consistent strength in the late childhood and adolescence. This conclusion partly contradicts the findings of Altemeier et al. [ 1 ], who claim that the effect of executive functions on academic performance may be more evident earlier in schooling, when academic skills are less automatic and require more effortful planning to execute. Similarly, some other studies point out inhibition as the strongest predictor of academic success at children’s early age such as that by Senn et al. [ 61 ]. They found out that while working memory contributed to academic success to a greater extent in older children, the inhibitory control did this in younger ones. Other authors [ 8 , 42 , etc.] mention the complete maturation of inhibitory processes by around the age of 12. The decrease in the potential of executive functions to predict academic performance during secondary education and even more so during university studies has also been touched upon by Pascual & Robres [ 57 ].

Methods used to measure the inhibitory control and the role of anterior cingulate

Scientists have developed several methods to measure inhibitory control, whose choice partly depends on the type of inhibition that is being targeted. Response inhibition, a term referring to the process of countermanding a prepotent motor response, has generally been assessed using non-selective stopping tasks such as the stop signal, go/no-go, and anti-saccade tasks. These tests require participants to intermittently suppress a motor response to a given presentation of a conditional stimulus or cue [ 6 , 20 , 71 , 73 ]. Attentional inhibition, which refers to the ability to resist interference from stimuli in the external environment, has been investigated using visual matching tasks requiring participants to judge whether target and comparison stimuli are the same or different and, at the same time, requiring them to ignore task-irrelevant distracters [ 36 , 68 , 71 ].

Response inhibition and attentional inhibition are also commonly measured with Stimulus-Response Compatibility tasks, such as the Eriksen Flanker (Flanker), Simon, and Stroop tasks [ 32 , 65 , 69 , 71 ]. The Stroop task (test) is utilized for comparing reaction times to stimuli in the condition where this control is not deployed (congruent condition) with the reaction times requiring inhibiting irrelevant stimuli (incongruent condition). The test has been shown to activate either the left dorsolateral prefrontal cortex or anterior cingulate for cognitive inhibition [ 74 ]. As Imbrosciano & Berlach [ 43 ] point out, anterior cingulate is considered to be responsible for selecting an appropriate response when the brain is exposed to two conflicting conditions. Bush et al. [ 17 ] hypothesize that anterior cingulate dysfunction is responsible for producing core features of ADHD, namely inattention and impulsivity. Anterior cingulate activation has been linked to detection of conflict and its resolution [ 18 ] as well as to academic results in college students [ 40 ]. The last-named researchers investigated the activity of anterior cingulate in connection with the error-related negativity (ERN, an electrophysiological signal associated with the anterior cingulate monitoring process, occurring approximately 100 ms after an error is made) and found a correlation between the magnitude of ERN and undergraduate students’ academic performance suggesting that the error detection mechanism is stronger in the students who perform better at university. Veroude et al. [ 74 ] observed a positive correlation between average course grades and the activation of anterior cingulate cortex in freshmen enrolled in a medical college during cognitive inhibition on the Stroop task finding no relationship between the course grades and activation of the left dorsolateral prefrontal cortex. Similarly, there are other studies which suggest a link between inhibitory control and academic performance associating the activation of anterior cingulate with cognitive control across tasks (e.g [ 31 , 34 ]).

The aim of the study

The aim of the study described in this paper was to find out whether there is any relationship between adult students’ inhibitory control measured with the Stroop Test and their academic achievement. To measure the degree of inhibitory control, a computerized version of the Stroop Test was used.

Based on the previous research (e.g. [ 29 , 40 , 55 , 57 , 74 ] the initial hypothesis was that there might be a relationship between inhibitory control and academic performance. In this respect, the participants with a higher degree of inhibitory control (lower Stroop Effect) were expected to be those with a higher grade average and lower failure rate than those indicating a lower degree of inhibitory control (higher Stroop Effect). On the other hand, if the correlation between the two variables were to be found, it was not expected to be significantly high since the previous research studying this phenomenon in relation to age points to the inhibitory control exerting its influence on academic performance chiefly at an individual’s young age [ 1 , 4 , 9 , 19 , 28 , 76 ].

Participants

107 students studying at (undisclosed) University, Stockholm, Sweden, (29 males, 78 females, mean age = 25.83 years, SD age = 6.32 years, age range = 19–52 years) participated in the study. Originally, 110 students were involved in the study, but 3 of them were removed as outliers due to the overwhelming majority of their grades being at the extreme ends of the grading scale, i.e. either VGs or Us, and only few Gs (for more information on the grading scale, see the next section). This was done to exclude the students whose extraordinary performance in certain academic subjects might be due to either their extra talents for, or their exceptional motivation to study, these subjects. The participants were recruited from students each of whom was enrolled in one of three teacher education programs, i.e. either primary ( N  = 21), secondary ( N  = 51), or upper secondary ( N  = 35). The reason why the participants were recruited from this group was that most of the courses they study within these programs are somewhat similar in terms of contents. Besides, the students are also assessed in these courses mainly by the same teachers. The original idea was to recruit the highest number of volunteers enrolled in the three programs who were, at the same time, studying the courses given by the department in which the study was conducted. Nevertheless, the final number of the participants was determined by their willingness to participate in the study and it was also restricted by the fact that all of them had to be tested on campus in a computer laboratory within the limited time of the project. The volunteers had no neurological or psychiatric disorders. All the participants signed an informed consent with their participation in the study.

Data collection and analysis

Information about the participants’ age and sex was collected via questionnaires distributed among the participants prior to the execution of the Stroop Test. The students’ university grade averages were computed based on their past course grades and their calculation included a computational model (see below) used in another study [ 30 ] researching the effect of mother tongue proficiency on the students’ academic performance.

The study was conducted in an institution using the grading scale consisting of three grades, i.e. VG, G, and U, a system commonly used in Swedish universities. According to this system, VG represents “passed with distinction,” G denotes “passed,” and U denotes “failed.” To facilitate a statistical analysis, these grades were assigned numerical values of 4, 2, and 0, respectively. This approach mirrors the GPA calculation method, where the highest grade corresponds to 4, the middle one to 2, and the fail grade to 0. Each student’s failure rate, expressed as a percentage, was computed as the ratio of their fail grades (Us) to the total number of grades received. Approximately 30 grades, encompassing both courses and graded modules, were considered for the computation of grade averages and failure rates per student. In instances where a student received multiple fail grades for the same course or module, each of these was included as a distinct grade in the calculation.

To measure the participants’ inhibitory control, a computerized version of the Stroop Test available at https://www.psytoolkit.org/ was used. The task was performed in English since the students represent a relatively uniform group when it comes to their English knowledge, which is at the C1 level of Common European Framework of Reference for languages. Moreover, English represents the language that all the participants have studied in a language instructional setting and thus the color identification rule in the Stroop test had to be followed in the context of their knowledge previously adopted at school. In this respect, the experiment made the participants deploy controlled information processing [ 63 ] through the application of a new cognitive concept requiring the inhibition of the semantic contents they have learnt at school before. This way an attempt was made at inducing the situation activating those cognitive processes that resemble the ones which are in operation in school environments when new concepts are learnt or when adjustments are made to the already acquired knowledge.

The task consisted of two conditions on which the participants were tested: (a) congruent trials, where the names of colors displayed on the screen matched the colors these were displayed in, (b) incongruent trails, where the names of colors displayed on the screen did not match the colors these were displayed in. For each trial type the students were instructed to identify the color of the word as quickly as possible by pressing a corresponding key on their keyboards. The keys the subjects were instructed to press were those that bore the initial letters of the names of the colors the words were displayed in. Therefore, when the word “red”, for instance, got displayed in blue, the students were supposed to press the b key (“b” standing for “blue”). The explicit instruction given to the students was to disregard the meaning of the words and focus solely on the color in which these words were displayed.

There were four colors used in the test (red, yellow, blue and green) and the students were instructed to press the r , y , b and g keys, respectively, to indicate these. Before each of the words was presented in the middle of the screen against the black background (for up to 2 s or until the participant responded), a fixation cross was displayed in the same position for 200 milliseconds for the participant to know where the word would appear. Once the participant made their choice, either a word “correct” or “wrong” popped up for 500 milliseconds depending on whether their choice had been correct or not. The computer script in which the test was run measured the participants’ reaction times in both the congruent and incongruent conditions and counted the errors they made when indicating a wrong color. The Stroop test was run under these conditions twice – once as a practice session with thirty trials, whose purpose was to make sure all the participants understood what they were supposed to do as well as to enable them to practice the key-color associations, and then as the test itself with 120 test trials. Half of the test trials were in the congruent condition and the other half in the incongruent one. The congruent and incongruent conditions were mixed and presented to the subjects randomly.

The main Stroop effect size was calculated for the individual participants according to the following formula using the reaction times recorded for congruent as well as incongruent trials:

The reaction times used in the formula above were collected together with the numbers of incorrect color identifications from files saved on a server once the tests had been completed.

Subsequently, Pearson’s bivariate correlation analysis was conducted on the collected data to find out the correlation coefficients between the participants’ grade averages (as well as failure rates) and their Stroop Effect values. Similar analyses were also done for their reaction times in congruent and incongruent conditions as well as their number of Stroop Test mistakes, i.e. the situations where a color was not correctly identified.

As the study group the analysis was conducted with consisted of three sub-groups of students (each sub-group consisting of students enrolled in one of the three teacher training programs), One-Way ANOVA was used to compare these sub-groups for Stroop Effect, reaction times for congruent trials, reaction times for incongruent trials, and number of color identification errors. Since the sub-groups were of unequal sizes, the test of homogeneity of variances was run on all the variables with the subsequent Tukey HSD post hoc test to identify the significance of the differences between the sub-groups.

The students’ ( N  = 107) mean Stroop Effect, mean reaction times (in ms) in congruent and incongruent conditions, the mean number of errors as well as the mean number of times the participants exceeded the time limit are given in Table  1 below. The table also lists students’ grade average and fail rate average as well as standard deviations for each variable.

Pearson’s bivariate correlation analysis shows a very weak negative correlation of low statistical significance, r (107) = − 0.13, p  = .20, between the Stroop Effect and participants’ grade averages and basically no correlation between the former and participants’ fail rate, r (107) = 0.04, p  = .68, (see Table  2 below). Similarly, there seems to be no statistically significant relationship between the participants’ grade averages and their reaction times in congruent ( r (107) = − 0.06, p  = .58) and incongruent ( r (107) = − 0.10, p  = .31) conditions as well as no significant relationship between the grade averages and the number of times the participants exceeded the time limit for color identification ( r (107) = − 0.07, p  = .46). The only statistically significant relationship detected appears to be the one between the students’ grade averages and the number of mistakes (incorrect color identifications) made during the Stroop Test with a weak negative correlation, r (107) = − 0.21, p  = .03. Scatter plots for Stroop Effect values and the number of errors made during the test in relation to the students’ grades are shown in Figs.  1 and 2 below. The diagonal lines in the scatter plots represent identity lines indicating the points in which the values of the variables correlate perfectly while the distances of the data points from these lines represent degrees of correlation; the closer the points are to the line, the stronger the correlation between the variables. Tables 3 and 4 show the comparison of measured variables across the educational programs and related post hoc Tukey HSD, respectively.

Grade average – Stroop Effect scatter plot

Grade average – Stroop Test errors scatter plot

The Tukey HSD post hoc test (see Table  4 below) shows the comparison of the distribution of the values within the sub-groups, where the only statistically significant Stroop Effect mean difference of 74.65 ms ( p  = .002) can be found between the primary and upper-secondary programs (the students of the latter indicating a lower mean).

The goal of this study was to find out whether there was some relationship between the inhibitory control of the students studying at (undisclosed) University, Stockholm, Sweden, measured with the Stroop Test and their academic performance. Based on the previous research focusing on links between school performance and executive functions [ 51 , 70 , 75 ], the hypothesis was that the participants with a higher grade average and lower fail rate might tend to manifest a higher degree of inhibitory control indicated with a lower Stroop Effect. Nevertheless, this correlation was expected to be weak in the study group consisting of university students since the other research into the area shows the strongest correlation between the inhibitory control and the academic performance in subjects at their early age [ 8 , 10 , 15 , 42 , 61 ].

The results show that although there is a very weak negative correlation ( r (107) = − 0.13) between the Stroop Effect and participants’ grade averages, which might suggest some effect of the degree of their inhibitory control on their school performance that is in line with the previous research focusing on this phenomenon, this relationship has not turned out to be statistically significant ( p  = .20). As regards the students’ failure rates, these turned out to be completely independent of the Stroop Effect values.

As regards the comparison of the distribution of all the observed values within the different sub-groups of students depending on what program they study, the only statistically significant difference was found in Stroop Effect (mean difference of 74.65 ms ( p  = .002)) between the primary and upper-secondary programs, with the latter indicating a lower Stroop effect.

Another statistically significant relationship detected was the one between the students’ grade averages and the number of mistakes (incorrect color identifications) made during the Stroop Test with a weak negative correlation ( r (107) = − 0.21, p  = .03) indicating that the students performing worse academically (having lower grades) made more mistakes during the test. This relationship may suggest that the degree of conscientiousness the students approach the assigned task of Stroop Test with might be in direct proportion to the degree of conscientiousness they approach their university studies with in general. That is [ 41 ], point out that conscientiousness predicts better performance on the Stroop task in terms of fewer errors and diminished incongruency effects. They even suggest that this personality trait may promote certain attentional processes even as cognitive capacities decline at a later age. Similarly, other studies [ 45 , 67 ], deploying other attention control tasks, also found a relationship between conscientiousness and cognitive performance. Finally, as the myriad of studies shows conscientiousness, defined as dependability and will to achieve, as being in direct relationship with academic performance as well [ 21 , 23 , 24 , 58 , etc.], the results of the study described in this paper might be indicative of the newly found relationship between the number of color identification errors (as a factor reflecting this conscientiousness) and academic performance, albeit this relationship has not been studied before.

One of the reasons why the weak correlation between the students’ Stroop Effect and their school performance shows low statistical significance may be that the grade averages had been calculated from the grades the students obtained for a wide range of school subjects ranging from mathematics, to languages, history, etc. That is, the meta-analysis conducted by Pascual & Robres [ 57 ] shows that the degree to which executive functions affect school performance depends on the subject studied. This phenomenon can be observed, for example, in the relationship between mathematics and the visuo-spatial aspect of working memory. Similar observations have also been made when it comes to other executive functions, which appear to be more related to performance in mathematics than in a language, for instance. Moreover, the meta-analysis points out that most studies identify working memory as a better predictor of school performance than inhibition and that executive functions represent an important predictor of academic performance and future learning problems at an early age. However, the predictive capacity of executive functions in relation to academic performance seems to decrease during secondary education and even more so during university education, which might be the case with the study described in this article. The reason for this phenomenon could be minimal individual differences in executive functioning in certain age groups. Bialystok [ 12 ], for instance, in her study of the Stroop task performance, mentions no differences in Stroop Effect among university undergraduates giving the cognitive performance in this age group being at its peak as a reason for the phenomenon. Likewise, Comalli et al. [ 22 ] demonstrated that older adults and children indicate longer response latencies than young adults. The aforementioned factors are also suspected of being the reasons why no correlation has been found between the students’ Stroop Effect and their failure rates.

The fact that the relationship between the students’ Stroop Effect and school performance shows low statistical significance might also be due to the Stroop Test activating different regions of the brain in different individuals – operations that have been documented as correlating with school grades. That is, Veroude et al. [ 74 ] report a significant main effect of cognitive inhibition being observed in the left dorsolateral prefrontal cortex, but not so much in the dorsal anterior cingulate cortex (ACC). However, they report the activation of ACC for the “incongruent” condition being associated with higher grades. In this respect, they found an association with achievement only in the situations where the Stroop Test activated dorsal ACC, indicating that “involvement of this region can potentially predict differences in education success.” (p. 104). Other studies also show the involvement of both the ACC and dorsolateral prefrontal cortex during the Stroop task (e.g [ 47 ]). even though the ACC does not seem to be necessary for cognitive control as patients with damage to this region perform normally on the Stroop Test [ 35 ]. As the study described in this paper did not include functional magnetic resonance imaging, it was not possible to find out in which situations the inhibitory control in the subjects in incongruent conditions resulted from the activation of the ACC and in which situations it resulted from the activation of the dorsolateral prefrontal cortex. Hence, it is also impossible to assess the extent to which the activation of the former or the latter for inhibitory control might influence the subjects’ grades. Not distinguishing between these two conditions could thus have been one of the reasons for the weak p-value of the results and thus it might be desirable to differentiate between them in future research.

Finally, as the current study suggests a link between the number of mistakes made during the Stroop Test and the students’ grade averages, the potential of the test to be used to measure the degree of their manifested conscientiousness and the ability to concentrate on an assigned, relatively short, one-off task should be studied further. The results of such further testing might provide clues regarding to what extent these characteristics can be viewed as predictors of academic performance.

Overall, this study has shown that there was a weak correlation of low statistical significance between the participants’ grade averages and the inhibitory control measured with the Stroop Test. It has also shown no relationship between their failure rates and inhibitory control.

These findings suggest that differences in the impact of inhibitory control on cognitive functioning among young adults might be much smaller, if any, than in children or older people. This fact seems to be in line with the findings of previous studies which point out that individual differences in executive functions are greatest while these functions are either under development, i.e. in children, or when they are in decline, i.e. in the elderly.

The study has also revealed that the students with lower grades made more color identification errors than those with higher grades. This phenomenon is worth pursuing in the future since the Stroop Test, or any other test where subjects need to follow a relatively simple rule, might be indicative (via their error rates) of their conscientiousness, a way in which they approach a certain assigned task or a degree of their ability to handle the task. Consequently, these findings can offer educators insights into their students’ specific weaknesses in these domains, empowering them to address these areas through tailored teaching approaches, such as individualized activities.

Data availability

The data pertinent to this study and used in the analysis are enclosed in a separate file uploaded at the submission of the paper.

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Dvorak, M. Inhibitory control and academic achievement – a study of the relationship between Stroop Effect and university students’ academic performance. BMC Psychol 12 , 498 (2024). https://doi.org/10.1186/s40359-024-01984-3

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Impact of blended teaching on academic achievement and well-being in operating room students: a semi-experimental study

• Somayeh Gheysari   ORCID: orcid.org/0000-0002-7212-3937 1 ,
• Mehdi Hasanshahi   ORCID: orcid.org/0000-0002-6377-1537 1 ,
• Parvin Ghaemmaghami   ORCID: orcid.org/0000-0002-7617-9815 2 &
• Fatemeh Vizeshfar   ORCID: orcid.org/0000-0003-1261-7318 3  

BMC Nursing volume  23 , Article number:  697 ( 2024 ) Cite this article

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Various virtual education methods, in addition to encouraging student-centered learning, positively impact the development of personal capabilities and improvement of students’ personality growth, especially when e-learning is combined with traditional education.

The present study is a semi-experimental study that Impact of Blended Teaching on Academic Achievement and Well-being in Operating Room Students.

This semi-experimental study, conducted over one academic semester, involved pre-test and post-test assessments with 44 operating room students in two university centers. Participants were selected through a census method and assigned to control and intervention groups. Data collection tools included the Hermance’s Academic Achievement and Hein’s Academic Well-being questionnaires.

The results of this study indicated a statistically significant difference in the level of well-being before and after the intervention, demonstrating a significant improvement in well-being in the Blended Teaching group after the intervention ( P  < 0.01). Independent t-tests showed no statistically significant difference in the mean score of academic achievement between the two groups after the intervention.

Based on the results of this study, blended teaching led to an increase in academic well-being in undergraduate students. To improve the level of academic well-being of students, educational policy makers should consider ways to educate students about new educational approaches. Prioritizing strategies in using educational methods may enhance academic well-being and leading to positive educational outcomes and fostering qualified and competent care in the nursing profession. Teaching clinical skills needs repetition, daily practice and continuous use to be internalized and become a habit. It may be that due to the short period of time and the absence of the first-semester students in clinical courses and fields, the level of academic achievement of the students did not show any particular change. It is suggested that more studies be conducted on comparing the use of this method with other self-centered and active training methods with a larger sample size.

Peer Review reports

One of the most important tasks of universities in promoting and improving the health, hygiene, and medical sectors is the training of skilled and efficient human resources [ 1 ]. Clinical education is a fundamental component of medical sciences education, playing a vital role in increasing and enhancing students’ professional skills and capabilities [ 2 ]. Clinical education environments are not planned and predictable like theoretical training environments and consist of psychomotor aspects and various variables in the field of knowledge and attitude [ 3 ]. Students in this environment must acquire sufficient skills in addition to acquiring knowledge, but the process of converting theoretical knowledge into practical knowledge is not simple, because teaching and learning in special clinical environments such as the operating room is more complex and different than other clinical environments [ 4 , 5 ] In the operating room environment where complex health care is required, students face many problems in applying the theoretical knowledge and skills that have been taught to them theoretically [ 6 ]. In this regard, adopting innovative methods in clinical education is one of the necessities for educational institutions and universities [ 7 ].

Various teaching methods in the clinical education environment contribute to developing students’ clinical skills and preparing them for entry into their professional environment, namely hospitals [ 8 , 9 ]. During education, the choice of teaching method plays a crucial role in students’ overall learning. Lecture-based teaching has a long history as a dominant method in educational systems [ 10 ]. In direct teaching or lecturing, the instructor takes a central role in presenting skills and patterns, and with the delivery of educational content, the main responsibility for managing the class lies with them [ 11 ]. This method results in the accumulation of knowledge with limited retention and does not foster creative individuals with critical thinking and problem-solving skills facing various challenges in educational systems [ 12 ]. Innovative and student-centered learning methods have become essential for educational systems [ 13 ].

These methods will promote the flexibility of educational courses and facilitate interactions, something not easily achievable in traditional classroom settings [ 14 ]. Students in the operating room technology experience high levels of stress in clinical education due to the nature of their discipline, which significantly impacts their learning and professional performance [ 15 ]. Factors such as instructor, surgeon, operating room personnel, large number of students, and patients, variety of surgeries, work pressure, speed and accuracy in performing activities and emergency conditions can affect the educational process in the operating room [ 16 , 17 ]. The main goal of any clinical experience is to bring students to the highest level of learning [ 7 ]. In various studies, one of the suggested solutions to enhance clinical skills in students, which has been used in some cases, is the use of blended teaching methods [ 18 , 19 ].

As a direct teaching method, blended teaching has garnered attention in educational patterns over the past few decades [ 20 , 21 , 22 ]. Blended teaching involves combining two or more teaching approaches [ 19 ]. This method makes online learning resources accessible to students and integrates instructional techniques with opportunities for online participation [ 23 ]. Blended teaching utilizes various tools, such as web-based technology, learning portals, video conferences, mobile applications, and many free websites [ 20 , 24 ]. Furthermore, in this context, the quality of education and excellent infrastructures, such as computers and the adoption of modern information technology equipment, are currently in high demand, leading universities to adapt their educational models using intellectual capital [ 25 , 26 ].Various studies suggest that mobile technology, virtual education, and incorporating videos, animations, visual designs, and text into cohesive content benefit students’ learning [ 27 , 28 , 29 , 30 ].

Given students’ inclination to use various virtual learning methods, applications, posters, and educational videos, in addition to encouraging student-centered learning, have a positive impact on improving clinical skills and competencies and reinforcing theoretical concepts, especially when combining electronic and face-to-face education. The ultimate goal of any successful educational system is the success of university students, which includes gaining appropriate experiences in all cognitive, emotional, social, behavioral, and biological dimensions. Today, due to its flexibility, timeliness, and continuous effectiveness in learning, blended teaching is the most effective and popular teaching method educational institutions use [ 31 ]. Therefore, it seems that blended teaching can contribute to student’s academic achievement and academic well-being by blended the strengths of electronic and face-to-face teaching methods.

One of the key indicators in evaluating educational systems is the students’ academic achievement [ 32 ]. Therefore, the effectiveness of an educational system is determined when the student’s academic achievement in various courses is satisfactory as the most important factor in social and individual success [ 33 , 34 ]. Academic achievement refers to the general or specialized knowledge or skills students acquire in the course content, which instructors often assess through various exams [ 35 ]. It indicates the extent to which individuals achieve goals and acquire mastery over a specific skill with a focus on educational activities [ 36 , 37 ]. This concept plays a crucial role in shaping an individual’s perspective on life as one of the important outcomes of educational performance [ 38 ]. According to the meta-analysis study by Bucker et al., academic achievement is associated with academic well-being [ 39 ]. In general, academic achievement and well-being serve as central indicators of positive psychological performance in identifying characteristics of high-performing educational systems [ 40 ].

Academic well-being is considered a new and comprehensive concept and one of the important indicators in evaluating educational systems [ 41 ]. According to the Ryff and Keyes (1995) well-being model, academic well-being includes various dimensions such as independence, mastery of the environment, personal growth, establishing positive relationships with others, having life goals, and self-acceptance [ 42 ]. Well-being relates to individuals’ feelings and thoughts about their lives [ 43 ]. In this regard, universities and higher education institutions not only play a role in acquiring academic skills by students but also provide an environment for individuals to experience all aspects of social life, including the ability to connect with others and develop their personalities, and subsequently contribute to improving academic well-being [ 40 ]. In the educational field, academic well-being is important as an internal control source, correlated with high self-esteem, intrinsic motivation, and positive or negative achievement [ 44 , 45 ].

While there is increasing evidence that various teaching methods affect academic achievement, learning, academic satisfaction, and other educational factors [ 46 , 47 , 48 , 49 , 50 ], However, there is a significant research gap in the effect of using blended methods in teaching clinical skills in relation to concepts such as academic achievement and academic well-being of medical students and especially operating room students. This gap is very important, because the provision of correct education improves the level of knowledge of learners. Fixing this research gap is very important because nowadays blended teaching is considered the most effective and popular educational method due to its effectiveness in flexible, timely and continuous learning. Today, educational systems face various challenges in academic planning and delivering educational content. In these circumstances, investigating the effects, advantages, and disadvantages of employing innovative teaching methods as an achievement in the transformation of modern educational systems is inevitable [ 51 ]. Therefore, assessing the effectiveness of education on student’s academic achievement, as the fundamental executive policy for achieving educational goals and learners’ growth, is essential. It is evident that adopting new teaching and learning methods is contingent upon a fundamental approach to educational research, and today, educational systems cannot be considered independent of research. Since new teaching methods need to be examined in various cultural, educational, and clinical contexts, conducting education research is deemed necessary. Proper education improves learners’ knowledge; subsequently, educating and training qualified and competent human resources through innovative and combined teaching methods prepares students to take on their real responsibilities in improving community health and enhancing the educational system. For this reason, the main goal of this research is to take a positive step towards advancing the objectives of the educational system by examining the Impact of Blended Teaching on Academic Achievement and Well-being in Operating Room Students.

Materials and methods

Design of the study.

The present research is a quasi-experimental intervention study with two groups, control and intervention, involving both pre-test and two post-tests.

Participants

The research environment was the schools offering undergraduate programs (bachelor’s) in the operating room at Shiraz University of Medical Sciences. The research population included all students admitted in 2022 who met the following criteria: being enrolled in the operating room major, having completed a maximum of two terms of previous studies, having taken the principles and techniques of Scrubbing and Circular course, having selected the course unit, and expressing a willingness to participate in the study. Exclusion criteria included absenteeism during the study, transferring to other universities, conditional status, and academic regression.

In this study, a total of 44 students accepted in the field of operating room for the entry of September 2022 participated. Since the number of bachelor’s degree students of operating room technology in most universities of the country is 20–30 in each entry, therefore, to avoid reducing the sample size, students from two faculties of Shiraz and Estahban were included in this study. At first, students of one university were selected as the intervention group and students of another university as the control group based on a simple random draw. In the following, students were allocated to intervention and control groups in a non-random manner and based on the attendance and absence list of the university where they studied. In this way, students who met the entry criteria were placed in two control groups (22 people) and intervention groups (22 people). The curriculum and educational content offered officially are the same in both colleges.

The process of randomizing student allocation based on universities serves as a methodological safeguard in educational research [ 52 ]. By employing randomization, researchers can mitigate selection bias and ensure that the sample is representative of the larger population of students across various institutions [ 53 ]. This approach is crucial when assessing educational interventions or outcomes that may be influenced by institutional characteristics such as teaching quality, resources available, and student demographics. The quality of evidence regarding the effectiveness of randomization in education stems from numerous studies indicating that randomized designs yield more reliable results than observational studies due to their ability to control for confounding factors effectively [ 54 ]. This method ensures that differences in performance can be attributed more confidently to the educational interventions being tested rather than pre-existing differences among students.

Implementation method of the study

In the Iranian educational system, the Operating Room major is an independent field of study. In their first academic term, students in this major choose the “Scrubbing and Circulating Skills” course, comprising two theoretical units and one practical unit. The practical part is conducted in the Clinical Skills Center.

The Clinical Skills Center, located in both faculties, offers similar equipment and facilities for practical training. The course is uniformly taught by professors across both faculties, ensuring consistency in the educational experience.

At the beginning of the semester, before any instructional interventions, a pre-test was administered to both groups of students. Each group received a set of questionnaires along with an informed consent form. The form outlined the research project’s objectives, assured the confidentiality of information, emphasized anonymity, and clarified the option to withdraw without affecting educational programs or relationships with instructors.

Throughout the sampling process, researchers, by explaining the research objectives and conducting multiple follow-ups, endeavored to enhance students’ willingness and collaboration in participating in the study. Subsequently, the educational content aimed at acquiring the necessary knowledge, awareness, and skills related to the duties of a scrub and circulating individual in various surgical procedures was delivered through 26 sessions. These comprised 20 theoretical sessions using a lecture-based method and six practical sessions lasting 2 h each, conducted in a practice room.

In the blended learning group, 18 virtual sessions were conducted, consisting of two theory sessions using a lecture-based method and six practical sessions at the Clinical Skills Center. The educational content covered various aspects, including familiarity with the department and surgical environment, patient admission in the operating room, understanding the surgical team’s responsibilities, principles of counting in the operating room, knowledge of operating room attire and personal protective equipment, care for pathological specimens, hemostasis methods, wound closure techniques in surgery, principles of prepping and preparing the patient’s skin before surgery, principles of draping, and how to scrub hands before surgery and donning gowns and gloves.

The theoretical content presented in the lectures was practically taught to the students at the Clinical Skills Center. After obtaining their consent, a local social networking application was installed on the students’ mobile phones to deliver the educational content through the created group, allowing the dissemination of texts, instructional videos, and posters related to skill training and operational principles in virtual (via social networks) and physical (in-class instructional video playback) formats.

At the end of each educational session, the control and intervention groups underwent immediate post-tests by completing questionnaires. Finally, a second post-test was administered to both groups one week after the intervention. It’s worth mentioning that electronic content was also provided to the control group at the end of the study to uphold ethical codes.

Data collection instruments

The data collection tools encompassed three key questionnaires: Demographic Information Questionnaire, Hermance’s Academic Achievement Questionnaire, and Heinz’s Academic Well-being Questionnaire. The questionnaires used are exactly the same English questionnaires that have been re-measured to ensure validity and reliability for students.

The sociodemographic and educational variables, including age, gender, academic term, place of residence, and interest level in the field of study, along with the following variables, were investigated.

Data collection tools

Academic achievement questionnaire.

The Hermanse Academic Achievement Questionnaire was utilized in this study to assess academic achievement. Hermanse (1970) reported correlation coefficients of each item with achievement motivation ranging from 30 to 57%. The reliability of the questionnaire was determined using Cronbach’s alpha as 0.84 [ 55 ]. This scale was reduced to 39 items in Iran by Homan and Asgari (1379) based on the reliability coefficient [ 56 ]. Each option is scored based on the intensity of academic achievement motivation, ranging from high to low or low to high. Responses are rated on a 4-point Likert scale (A [ 4 ] – B [ 3 ] – C [ 2 ] – D [ 1 ]). Higher scores indicate higher motivation for academic achievement, while lower scores suggest lower motivation. The score range is from 29 to 116, reflecting the spectrum of motivational changes.The scale’s homogeneity coefficient was 0.803 in a study by Hooman and Asgari (2000) on 1,073 students. Factor analysis identified seven factors (perseverance, self-confidence, time perception, opportunity-seeking, diligence, competence criteria in choosing friends, high aspiration level, and future orientation) with a factor loading of at least 0.3 [ 56 ]. Additionally, ShahbaniFar et al. calculated the reliability of this questionnaire using Cronbach’s alpha as 0.86 [ 57 ]. In the present study, the reliability of the academic achievement scale was confirmed with a Cronbach’s alpha coefficient of 0.81.

Academic well-being questionnaire

The Heinz Academic Well-being Questionnaire, designed and developed by Heinz in 1993 [ 58 ], was employed in this study to measure the academic well-being of students. This single-factor scale consists of 102 questions, utilizing a four-point Likert scale (completely agree, agree, disagree, strongly disagree) to assess academic well-being. Higher scores indicate higher levels of well-being, ranging between 102 and 408.

Due to the absence of validity and reliability information for the Academic Well-being Questionnaire, the questionnaire underwent a psychometric evaluation by the researchers before being used in this study.

Reliability and validity of academic well-being questionnaire

In this phase of the study, the content validity of the questionnaire was assessed through expert judgment [ 59 ]. They presented the questionnaire to 15 faculty members specializing in operating room and psychometricians to determine its qualitative face validity. The experts examined factors such as the difficulty level, appropriateness, and ambiguity of the questionnaire items. After refining the items and determining the importance of each one, the researchers employed a quantitative impact item analysis [ 60 , 61 ]. For the qualitative content validity assessment, the 15 experts provided feedback on the questionnaire’s adherence to grammar rules, use of appropriate terminology, and proper placement of phrases.

To quantitatively assess the content validity, the researchers used the Content Validity Ratio (CVR) and the Content Validity Index (CVI). The CVR was determined by asking the 15 specialists to review the items based on a three-part spectrum (essential, useful but not essential, not necessary). Items with a CVR value above 0.62 were considered significant and were retained [ 62 ].

The CVI was examined based on Waltz and Basel’s content validity index [ 61 ]. The researchers provided the questionnaire to the 15 specialists and asked them to assess each item’s relevance, clarity, simplicity, and specificity using a four-part Likert scale [ 63 ]. Items with a CVI score of 0.79 or higher were accepted [ 64 ].

After the content validity assessment, the research team removed 15 items from the questionnaire due to their CVR values being less than 0.62. The final questionnaire was approved with 87 items, and its reliability was assessed with a Cronbach’s alpha coefficient of 0.86. Overall, the researchers utilized both qualitative and quantitative methods to thoroughly assess the content validity of the questionnaire, ensuring its appropriateness and reliability for use in the study.

Data Analysis

The collected data were analyzed using the SPSS software, and statistical significance was determined at P  < 0.05 through descriptive and inferential statistics. The Shapiro-Wilk test was employed to assess the normality of the data. Considering the normal distribution, independent t-test and Chi-square test were used to compare the two groups regarding demographic data.

Repeated Measures Analysis of Variance (ANOVA) was used to analyze the mean scores of academic well-being and academic achievement in the two groups at three different time points. Post hoc comparisons were performed using the Bonferroni post hoc test.

Table  1 provides the demographic characteristics of the study population. Based on the table descriptions, it can be observed that most individuals are male (30 individuals, 68.2%), and the remaining are female. Furthermore, most individuals are single and live with their families, with approximately all individuals (41 individuals, 93.2%) expressing an interest in their field of study. The two groups did not exhibit significant differences in terms of demographic characteristics, residence, and interest in the major ( p  > 0.05) [Table  1 ].

Table  2 compares academic well-being within and between the two groups at three different time points. The t-test indicates that before the intervention, there was no statistically significant difference in academic well-being between the two groups ( P  < 0.06 and P  < 0.2). The Repeated Measures Analysis of Variance (ANOVA) immediately and one week after the intervention shows a statistically significant difference in the mean scores of academic well-being between the intervention and control groups, with the intervention group having higher mean scores ( P  < 0.01). The within-group comparison also reveals that the intervention group had significantly higher mean scores of academic well-being ( P  < 0.004). Table  2 presents a comparison within and between the two groups before, after, and one week after the intervention.

The Bonferroni test was employed for pairwise comparisons across the three stages. However, due to the lack of significance in well-being means within the control group, there is no necessity to explore pairwise comparisons of the time points in that group. The pairwise comparisons of time points within the control group did not yield statistically significant results, indicating that the well-being level in the control group remained relatively stable over time. A statistically significant comparison was observed in the intervention group between pre-intervention and post-intervention, signifying a notable improvement in well-being after the intervention ( P  < 0.015). Notably, the well-being level in the intervention group exhibited a significant increase one week after compared to pre-intervention. In contrast, in all other pairwise comparisons, no significant differences were observed between the two time periods [Table  3 ].

Furthermore, the independent t-test indicated that the mean score for academic achievement did not exhibit a significant difference between the two groups before, immediately, and a week after the intervention ( P  = 0.976, P  = 0.914, and P  = 0.257). Additionally, repeated measures of ANOVA were employed separately in each group to assess the mean score of academic achievement among the subjects before, immediately, and a week after the intervention. According to the results of this test, the difference in the mean scores across the three stages was not statistically significant [Table  4 ].

In both groups, there is no significant difference in the pattern of academic achievement mean scores across the three-time points. As a result, there is no necessity for pairwise comparisons.

Blended teaching, as one of the modern educational approaches, is important due to its utilization of innovative technologies and interaction applications in the learning process. Additionally, the concepts of academic achievement and academic well-being are considered significant motivational factors in learning [ 65 , 66 , 67 ]. Therefore, this research aims this research aims that Impact of Blended Teaching on Academic Achievement and Well-being in Operating Room Students.

According to the results of this study, the educational intervention led to an increase in academic well-being in the intervention group. As a comprehensive concept, academic well-being is an effective indicator in evaluating educational systems [ 68 ]. This result aligns with various studies in the field of academic well-being [ 69 , 70 , 71 ]. The findings suggest that one of the influential factors in the academic well-being of students is the implementation of necessary measures and initiatives for education and the execution of curriculum plans by instructors [ 68 , 72 ].

In this regard, the results of the study by Hietajärvi et al. (2019), aiming to examine the multidimensionality of digital social participation and its relationship with academic well-being in three educational stages, showed that the use of digital tools for acquiring and sharing knowledge reflects multiple dimensions that are related to academic well-being [ 73 ]. In their study, Huang et al. (2023), integrating participatory inquiry strategies and blended learning, stated that goal setting and task value determination play a significant role in the well-being of students [ 74 ].

The psychological dynamics in relation to academic well-being can be interpreted in various ways. It seems that a blended approach emphasizing multimedia and meta-learning can impact academic well-being. This approach combines the strengths of two teaching methods, lectures and virtual learning, to present educational content tailored to the learners’ situation and enhance the academic well-being of students. In this way, improving academic well-being may lead to better interaction with educational goals and achieving the desired educational outcomes [ 39 ].

Also, according to the results of this study, there was no statistically significant difference in academic achievement between the intervention group, which received blended teaching, and the control group, which received conventional education. Therefore, the educational intervention did not play a role in enhancing students’ motivation for academic achievement. This finding is consistent with the study’s results by Hinampas et al., which showed that blended teaching did not impact students’ academic achievement. They suggested that more variables related to the learning environment should be examined to identify factors that could lead to changes in academic achievement [ 75 ]. It appears that the students’ academic achievement depends on various factors, and identifying these factors, along with the use of innovative teaching methods, can contribute to achieving educational goals more effectively.

Contrary to the present study’s findings, various studies have reported a significant correlation between blended teaching and academic achievement [ 76 , 77 ]. Ceylan and Kesici, in their study, utilized a blended learning environment enriched with web technologies such as video conferencing, learning management systems, and supportive blogs for teaching students. The results indicated a significant difference in students’ academic achievement due to the blended teaching environment [ 78 ]. Blended teaching, through the enrichment of web technologies, seems to provide more effective learning outcomes. In their study, Kassab et al. (2015), which aimed to investigate the relationship between factors measuring the experience of blended teaching and the academic achievement of medical students, stated that the quality of teaching and appropriate workload significantly influences the motivational aspect of students.

According to the results of this study, high teaching quality was associated with increased self-efficacy, individual effort, mastery of content, and greater motivation for learning, ultimately leading to improved academic achievement among students by controlling internal and external factors [ 79 ]. In explaining this issue, it can be stated that various factors are influential while implementing blended learning increases students’ use of academic skills [ 80 , 81 ]. One aspect relates to the type of educational intervention, which in this study involved using instructional videos and posters related to teaching skills and operational principles, delivered virtually (via social networks) and in person (screening instructional videos in class). The results of the present study show that despite the introduction of blended teaching method aimed at enhancing student engagement and learning outcomes does not support a significant difference in academic achievement when compared to traditional instructional strategies. This suggests that factors influencing student success may extend beyond mere instructional methodology [ 82 ]; aspects such as student motivation, curriculum design, assessment strategies, and institutional support may play critical roles that warrant further investigation [ 83 ]. Thus, while educators may continue to explore innovative pedagogical approaches within their curricula, it is essential to recognize that substantial shifts in academic performance metrics may require more comprehensive systemic changes rather than simply altering teaching methodologies alone.

In general, various studies have investigated the effect of blended teaching on academic well-being. In these studies, the aspect of learners’ learning styles, the use of diverse methods of content presentation, the introduction of new technologies and platforms for learning, communication and the evaluation of the use of multimedia based on multisensory have had a positive effect on the well-being of students, because they It enables them to maintain a better balance between their studies and personal life and manage their time better [ 84 , 85 ]. However, planning to design and determine the important features of the blended teaching method can directly affect it. The results of Clarkson’s study on the effects of media tools related to blended teaching reported no significant difference in teaching quality and improved student academic performance [ 86 , 87 ]. In this regard, based on previous studies, the support of instructors in innovative teaching and learning by maintaining interactions significantly improves the level of academic progress. It seems that when students are motivated, they develop their personal and academic characteristics and are able to achieve a higher level of academic achievement. In fact, academic progress is influenced by various factors, including the way the training course is designed, the support of instructors, the training environment, innovative techniques and tools, the use of virtual reality technology, artificial intelligence, and project-based learning. In addition, the results also show that instructors should carefully consider the needs and preferences of students when designing courses and curricula in order to encourage and support students to achieve higher academic motivation [ 74 , 85 , 87 , 88 ].

The present study may increase our knowledge about the effect of blended teaching on academic well-being and academic achievement. The findings of this research have useful applications for planners and educational managers. It seems that the results of this research can be used in the educational programs of all medical and nursing students according to the educational content they need. The improvement of practical and attitudinal abilities will improve the clinical competence and professional performance of students, which subsequently, by using its benefits in different ways, it will be possible to benefit from the improvement of the health care system. Paying attention to the flexibility of the course structure, educational content according to the desired goals and controlling the speed of education in using the blended learning method is very important. It is important that the educational system and learners have a clear understanding of the concept and nature of blended learning skills to further develop it and improve the level of knowledge. These findings suggest important elements to consider when designing blended teaching courses in diverse student populations.

According to the results of this study, education using a blended teaching approach led to an increase in students’ academic well-being. Attention to this issue and using student-centered teaching methods can create a psychologically favorable environment for enhancing student education. It is worth mentioning that educational software and electronic learning resources, combined with traditional teaching methods and complementary education, can provide a suitable platform for improving individual capabilities and personal growth, yielding fruitful outcomes. Therefore, enhancing students’ academic well-being through mentoring programs, peer support groups, tutoring services, and opportunities for student engagement is recommended. Although the results of this study did not show a significant difference in the academic achievement of the two groups, considering that students’ academic achievement is an important criterion for enhancing the quality of education, it is also necessary to pay attention to this aspect. The small sample size due to the decrease in the number of entries in the field of operating room technology in the current academic year, and the lack of full review and study of the educational content (posters and educational videos) by the students had a great impact on the results of this study. However, using the blended learning method using posters and educational videos along with the lecture method in clinical education helps to create diversity in the educational methods and increases the attraction and learning of students. While the current study provides promising preliminary evidence, more research is needed to fully understand the application of the blended teaching method in the training of operating room students. Blended teaching can be used as an interactive tool to complement traditional teaching methods and provide more diverse learning opportunities to students. This can lead to a deeper understanding of concepts and improve learning.

Limitations

This study employed clinical skills training, which included cognitive, emotional, and psychomotor aspects. Since these skills require repetition, daily practice, and continuous use to become internalized and habitual, it is possible that, due to the short duration and the absence of first-semester students in clinical internships and fields, the students’ academic achievement level did not show a specific change. Another limitation of the study was the short intervention period. It is suggested that longer and longitudinal studies be conducted in this field. Also, in the present study, to prevent contamination, information about the intervention was not provided to the participants of the control group, and the subjects of the intervention group were instructed not to share any information about the educational resources. One of the other limitation of this study is the small number of sampled students due to the limited acceptance of students and the necessity of sampling among students who had chosen the scrub and circular skills course. Given the limited studies on the effectiveness of blended teaching methods on clinical skills learning, it is recommended that further research be conducted to compare the use of this method with other learner-centered and active teaching methods with a higher sample size. In this study, posters and educational videos were used to teach students along with the lecture method, which seems that using this blended method alone cannot practice a wide range of clinical skills and help improve academic achievement in be considered. Also, this educational method cannot put the student in direct clinical contact with the real clinical environment and helps to prepare them to face various conditions in the real environment. Thus, it is necessary to conduct more research to determine the effectiveness and efficiency of using the blended teaching method with educational videos in the training of operating room technology students. In addition, it is necessary to develop strategies for using this educational method along with other electronic education methods in existing educational programs.

Data availability

Upon request from the first author data is available ([email protected] ).

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Acknowledgements

The authors would like to thank Vice-chancellor of Shiraz University of Medical Sciences (grant No: 26177 ) for financial support. The authors thank all students who participated in the current study.

This study financially supported by the Vice-chancellor of research Shiraz University of Medical Sciences (Grant Number: 26177). The funder had no role in the design of the study, nor in the collection, analysis, and interpretation of the data and in writing the manuscript.

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Relationship between study habits and academic achievement in students of medical sciences in Kermanshah-Iran

Haleh jafari.

1 Clinical Research Development Center of Imam Reza Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran

Abbas Aghaei

2 Social Determinants of Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran

Alireza Khatony

3 Health Institute, Social Development and Health Promotion Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran

Study habits have been the most important predictor of academic performance and play a special role in the academic achievement of students. The aim of this study was to investigate the status of study habits and its relationship with academic achievement in medical sciences students in Kermanshah-Iran.

Materials and methods

This cross-sectional study was carried out on 380 medical sciences students at Kermanshah University of Medical Sciences. The samples were randomly assigned to the study. The Palsane and Sharma study Habit Inventory was the tool used for data collection. Data were analyzed by descriptive and inferential statistics.

The mean of students’ grade point average was 15.73±1.5 out of 20 and the mean of total status of study habits was 45.70±11.36 out of 90. The status of study habits in 81.3% of the students was at moderate level. There was a direct and significant relationship between study habits and academic achievement.

The status of study habits was at moderate level for most students. Therefore, it is recommended to consider and assess students’ study habits at the time of entry into university, in addition, specific training should be offered to students in order to help them learn or modify study habits to increase their academic achievements.

Introduction

Academic performance of students is one of the main indicators used to evaluate the quality of education in universities. 1 , 2 Academic performance is a complex process that is influenced by several factors, such as study habits. 2 Study habit is different individual behavior in relation to studying 3 and is a combination of study method and skill. 4 In other words, study habits include behaviors and skills that can increase motivation and convert the study into an effective process with high returns, which ultimately increases the learning. 5 This skill is also defined as any activity that facilitates the process of learning about a topic, solving the problems or memorizing part or all of the presented materials. 3 Study habits are in fact the gateway to success and differ from person to person. 4

According to previous studies, good study habits include studying in a quite place, studying daily, turning off devices that interfere with study (such as TV and mobile phones), taking notes of important content, having regular rests and breaks, listening to soft music, studying based on own learning style, and prioritizing the difficult contents. 6 Some of the worst study habits include procrastination, evading the study, studying in inappropriate conditions, and loud sound of music and television during studying. 7

Study habits are the most important predictor of academic performance and global research has revealed that study habits affect academic performance. 8 In this regard, medical students are faced with a large amount of information that is difficult to organize and learn, and requires knowledge and application of study skills. 5 , 9 Evidence suggests that learners who do not have enough information about study strategies do not attain effective and stable learning, and therefore will not have an appropriate level of academic achievement. 3 In other words, students with better academic achievement use these skills more than those with lower academic achievement. 10

Given the important role of study skills in a student’s academic achievement, today, many prestigious universities such as York University in Canada and University of Berkeley in California teach study skills to newly-enrolled students. 11 In different studies, study skills and habits and their relationship with students’ academic achievement have been studied and different results have been reported. 1 , 3 , 12 Also, various studies have reported the study habits of students from weak to desirable levels. 5 , 7 , 10 In this regard, a study conducted on study habits of students in 21 medical universities in Iran showed that 32% of the students suffered from a severe lack of study skills and habits. 10 In many studies, a positive and significant correlation has been found between students’ study habits and their academic achievement. 4 , 6 , 7 , 10 However, in Lawrence’s study, no significant relationship was found between these two variables. 1

Considering the importance of study skills and habits of students, and the important role they play in the academic achievement of students, and taking into account that study habits vary from person to person and from place to place, and also as the results of related studies are different from each other, the present study was designed and implemented. Our goal was to investigate the relationship between study habits and academic achievement of medical sciences students in Kermanshah University of Medical Sciences (KUMS), Iran.

Study design

The present study had a descriptive-analytical and cross-sectional design and was conducted between November 2017 and April 2018.

Study questions

We sought to answer the following questions: 1) what is the status of students’ study habits in terms of variables such as; faculty, place of study, academic degree, history of probation, status of residence, and gender? 2) what is the status of students’ academic achievement in terms of variables such as; faculty, place of study, academic degree, history of probation, status of residence, and gender? and 3) what is the relationship between the status of study habits and students’ academic achievement?

Sample and sampling method

PASS/11 software was used to calculate the sample size. For this purpose, according to the results of Nourian et al's study (2011), in which the highest standard error rate was 0.96, 11 the minimum sample size was calculated to be 328 individuals with the first type error of 0.05, and the accuracy limitation of estimated mean of 1 unit. Considering the 15% probability of not responding, 380 students were enrolled in the study. The samples were selected randomly from different faculties of KUMS, which included the faculties of medicine, nursing and midwifery, dentistry, paramedicine, pharmacology, and health. The sampling classes were formed by the faculties of the university. In each class, proportional to the size of students, numbers of samples were selected randomly using a random table of numbers. Accordingly, the sample size for each faculty was as follows: medical school =130 students, dentistry =20, pharmacology =30, health =50, nursing and midwifery =50, and paramedicine =100 students. Inclusion criteria included willingness to participate in the study and studying at the second term and above. Exclusion criteria were absence on sampling day and failure to answer all questionnaire questions.

Measurement instruments

The study tools consisted of individual data collection form and the Palsane and Sharma Study Habit Inventory (PSSHI). The individual information forms included questions about age, gender, marital status, faculty of study, academic degree, history of probation, being native or non-native, and the grade point averages (GPAs) of the previous term(s).

The PSSHI is a standard tool designed by Palsane and Sharma in India (1989) 10 and its reliability is higher than that of other study habits questionnaires. 13 Validity and reliability of the original version of this questionnaire have been confirmed in previous studies. 10 , 14 , 15 Siahi and Maiyo (2015) reported the reliability coefficient of 0.88 for the PSSHI. 7 The reliability coefficient of the Persian version of this tool has also been reported as 0.88. 10 In the current study, content validity analysis was used to determine the validity of the instrument. For this purpose, the questionnaire was distributed among 12 panels of experts at KUMS. They were asked to review the questionnaire in terms of fluency, clarity, and relevance. It was then modified based on their opinions. Test-retest method was used to examine the reliability of the PSSHI. In this regard, the questionnaire was distributed among 20 students, and after a 2-week interval, they were asked to answer the questionnaire. Correlation coefficient of the pre-test and post-test scores was 0.87, which was acceptable.

PSSHI has 45 questions and measures the study habits of students in eight areas, including time management (five items), eg, “I study at a specific time of the day.”; physical conditions (six items), eg, “I get disappointed by the noise around me.”; learning motivation (six items), eg, “if I do not understand something, I get help from others.”; reading ability (eight items), eg, “before reading the intended chapter, I read its main points.”; note-taking (three items), eg, “I take notes while reading the text.”; memory (four items), eg, “I read some materials without sufficient understanding.”; taking tests (ten items), eg, “before responding to the test questions, I read all the questions first.” and health of study (three items), eg, “if the result of the test is not good, I feel disappointed.” Responses are based on a three-option Likert scale that includes: “always or most of the time”, “sometimes”, and “rarely or never” which are graded from two to zero, respectively. Questions 6, 9, 13, 15, 24, 26, 34, 36, 37, 41, and 42 are scored inversely. The score range of the questionnaire is between 0 and 90, and a score of 60 and above reflects a desirable level of study habits, a score of 31–60 indicates relatively good or moderate level of study habits, and a score of 30 or below refers to an undesirable level of study habits. The score range for each of the sub-categories is as follows: time management: 0–10; physical conditions: 0–12; learning motivation: 0–12; reading ability: 0–16; note-taking: 0–6; memory: 0–8; taking tests: 0–20, and health of study: 0–6. The achieved score for each sub-category was computed using the three-part spectrum method. To do this, the lowest score was subtracted from the highest score and the resulting number was divided by 3. The resulting number was the distance of three grades which indicates the desirable, relatively desirable, and undesirable levels of each sub-category.

To assess academic achievement, the GPA(s) of the previous term(s) was used, which in the Iranian educational system is from 0–20. For this purpose, a GPA of 17 or higher was considered as “good academic achievement”, 14–16.99 as “moderate educational achievement”, and a GPS of less than 13.99 was considered as “poor educational achievement”.

Data collection method

First, permission to conduct the study was obtained from the KUMS Deputy for Research and Technology, and was presented to the authorities of the affiliated faculties. In the next step, the list of students in each faculty was taken from the Department of Education and samples from each faculty were selected. Then, according to the classroom schedules, the selected samples were approached and after explaining the purpose of the study to them, a copy of the questionnaire was given to those who agreed to take part in the study. If any of the samples did not want to continue participating in the study, he/she was replaced by a person above or below him/her in the list. The questionnaires were collected by the researcher after completion.

Data analysis

Data were analyzed using 18th version of the Statistical Package for Social Sciences (SPSS v.18.0; SPSS Inc., Chicago, IL, USA). Descriptive and inferential statistics were used to analyze the data. At first, Kolmogorov-Smirnov test was used to assess the normality of the data, which showed that academic achievement of students did not have a normal distribution, but the rating of study habits had a normal distribution. Mann–Whitney U test was used to compare academic achievement in terms of dual-mode qualitative variables (such as gender and marital status), and Kruskal-Wallis H test was used to compare academic achievement in terms of multi-mode qualitative variables (such as academic degree and faculty of study). Pearson correlation coefficient was used to evaluate academic achievement in terms of quantitative variables. The t -test was used to compare the mean of study habits in terms of dual-mode qualitative variables (gender and marital status) and ANOVA was used to compare the mean of study habits in terms of multi-mode qualitative variables (such as academic degree and faculty of study). Pearson correlation coefficient was used to investigate the relationship between academic achievement and study habits. p -values less than 0.05 were considered as significant.

The study was approved by the Ethical Review committee of the Kermanshah University of Medical Science with code: KUMS.REC.1395.292. Objectives of the study were explained to the participants and they were assured about the confidentiality of their information and their responses. Iinformed written consent was also obtained from all participants.

Of the 380 students participating in this study, 65.3% (n=248) were male and 34.3% (n=132) were female. The mean age of the students was 22.26±2.9 years. Most of the students were single (91.1%, n=346), and had no history of probation (92.1%, n=350). The majority of the students were from faculties of medicine (34.2%, n=130) and paramedicine (26.3%, n=100). Most students were studying at doctoral (47.4%, n=180) and undergraduate (45.5%, n=173) levels. They were also mainly native students (59.2%, n=225), ( Table 1 ).

Demographic variables and comparison of the academic performance and study habits based on underlying variables

Notes: * Independent t -test; ** ANOVA; *** Mann-Whitney U test; **** kruskal-Wallis H test; † non-significant.

The mean score of students’ study habits was 45.7±11.36 out of 90. In terms of study habits, only 10% (n=38) were on a desirable level and 81.3% (n=309) were on a moderate level. Also, 8.7% (n=33) of them were on an undesirable level. In terms of the eight areas of study habits, the status of most students was undesirable in the areas of taking notes (50.2%, n=191) and well-being (48%, n=182), and was desirable in the area of time (27.3%, n=104). The status of most students in the other areas was moderate ( Table 2 ).

Frequency of subcategories of students’ study habits

The mean of students’ total GPA of the term(s) was considered as an indicator of academic achievement, which was 15.73±1.5 out of 20. The highest and lowest levels of academic achievement were respectively for the students in faculties of health and medicine with a mean and SD of 16.27±1.48 and 15.08±1.39 respectively, which showed a statistically significant difference ( p <0.001). The highest and lowest levels of academic achievement were respectively related to the MSc and doctoral students with a mean and SD of 16.98±1.61 and 15.19±1.38 respectively, which showed a statistically significant difference ( p <0.001). Academic achievement in students without history of probation was significantly higher than those with history of probation with a mean and SD of 15.86±1.42 and 14.20±1.67, respectively ( p <0.001). Female students had better academic achievement compared to male students with a mean and SD of 16.15±1.34 and ±15.5±1.5, respectively. This difference was statistically significant ( p <0.001), ( Table 1 ).

The results showed that, students of the faculty of nursing and midwifery and the faculty of dentistry had the highest and the lowest mean of study habits with mean and SD of 48.66±9.63 and 43.20±12.58 respectively, which was not statistically significant. In terms of academic degree, MSc and undergraduate students had the highest and lowest average of study habits, with a mean and SD of 57±11.34 and 44.52±11.99 respectively, which was not statistically significant. Students without history of probation had a significantly better status of study habits compared to students with probation history ( p <0.001), with a mean and SD of 46.16±11.04 and 40.33±13.69, respectively. The results showed that the status of study habits of female students was better than that of male students respectively, with a mean and SD of 46.68±9.91 and 45.18±12.05 respectively, but this difference was not statistically significant. Native students had significantly better status of study habits compared to dormitory students ( p <0.001), with a mean and SD of 46.98±10.67 and 43.58±12.23, respectively.

Pearson correlation test showed a direct and significant relationship between academic achievement and study habits (r=0.235, p <0.001).

In our study, the status of study habits of most students was at moderate level and only one tenth of the students were at the desirable level. Mendezabal (2013), in a study that investigated the study habits of 239 Filipino students, reported their study habits to be at moderate level, which indicated insufficient and ineffective study skills. 12 On the other hand, the results of a study conducted on librarian students in Iran indicated the general level of students’ study habits to be 60.5 out of 100. 5 Although the level of study habits in this study was moderate, this level was higher in our study, which may be due to the differences in the nature of medical sciences and librarian academic programs. In another study that Garner (2013) conducted on 59 undergraduate chemistry students in West Indies, the level of study habits was at desirable level in 59.2% of the students, and this level was poor in the rest. 16 The difference between the results of this study and our study could be due to the low numbers of participants in Garner’s study and the differences in the tool used to measure study habits, because the tool used in Garner’s study classified study habits into two good and poor level and eliminated the intermediate level, which might have reduced the accuracy of data and comparative capability of the study.

In our study, in terms of eight areas of study habits, the status of study habits in most students was undesirable in the areas of taking notes and well-being, and was desirable in the area of time. The status of study habits in most students in the other areas was at moderate level. Regarding the different areas of study habits, the results of studies are varied. In this regard, the result of a study conducted on 150 nursing students in Iran showed that most of the students’ problems were related to taking notes, reading ability, time management, well-being, memory, motivation, learning, physical condition, and taking tests. 22 In some studies, time management has been described as one of the major problems for medical students. 17 , 18 Mendezabal (2013) also referred to problems such as ineffective time management, lack of planning and concentration, poor study skills, and inadequate examination techniques. 12 The differences in the areas of study habits can be attributed to the individual differences between the samples and their previous educational systems.

In our study, the students in the faculties of nursing and midwifery and dentistry had the highest and the lowest mean study habits, respectively. This difference was not statistically significant. Despite the fact that this variable has not been discussed in most studies, this finding reflects the relatively similar level of study habits in the students of various medical sciences academic programs.

In our study, there was no significant difference between different educational levels in terms of the mean study habits. In other words, the level of study habits in different educational levels was equal. Our results are in line with the study of Fereydoonimoghadam and Cheraghian. 19 According to the authors of the present article, every student of medical sciences, regardless of what degree level he/she is studying at, should be aware of study skills and habits and how to apply them.

In the present study, students with no history of probation had significantly better status of study habits compared to the students with a history of probation. Despite the fact that many studies have not addressed this variable, Rezaie and Nourian in their studies, have pointed to a meaningful relationship between probation and poorer academic performance, and have considered study habits as an important factor influencing these variables. 10 , 11 In this regard, Khan (2016) described poor study habits as the most important reason for students’ academic failure. 20 In our view, students with poor academic performance, by utilizing the proper skills and study habits, can improve their academic performance and thereby prevent the emergence of educational problems, such as dropping academic unit/credits and probability of probation.

In our study, the status of study habits in male and female students did not differ from each other significantly, in other words, in terms of skills and study habits, male and female students were at the same level. Oli (2018), Hashemian (2014), and Torabi (2014) also did not find any significant difference between the students’ gender and study habits, 5 , 21 , 22 which can be due to the same educational environment for male and female students. In our view, every student, whether male or female, should be aware of study skills and habits and use them.

We found that native students had significantly better study habits compared to dormitory students. However, some studies did not report statistical significance between study habits and place of residence. 14 In our opinion, the conditions of place of residence, especially the place of study, play an important role in the study habits of students. Failure to observe the necessary standards in dormitories and the lack of suitable environment and conditions can have a negative effect on students’ performance.

We found a positive and significant correlation between academic performance and study habits, which is consistent with the results of studies by Fereydoonimoghadam and Cheraghian (2009), Alimohamadi (2018), and Rabia (2017). 13 , 19 , 23 However, Lawrence (2014) and Torabi (2014) did not find any significant statistical relationship between study habits and academic performance. 1 , 21 We believe that the utilization of study skills and habits can play a positive role in improving academic performance of students. Academic achievement and achieving educational goals require the existence of several factors, the most important of which is the study habits of individuals, 13 since the use of various and effective methods of study improves academic performance of students. Strengthening each of the eight areas of study skills can help to improve the academic performance of students, thus it is necessary to pay attention to these areas. Since academic performance is considered as a predictor of success in a person's career, it is important to pay attention to this issue and apply appropriate strategies to improve the study habits of students. Meanwhile, because of the high sensitivity of future professions in medical students, and the need for comprehensive learning of the curriculum, paying attention to the status of study habits and its promotion is critically important.

There are some limitations to this study. First, this was a cross-sectional study and according to the nature of cross-sectional studies, it is not possible to determine the causal relationships between study variables. Another limitation in this study was related to the data collection method, which was self-reporting. Despite reassuring the samples about the confidentiality of their responses, this approach might have had an impact on the accuracy of our results.

In our study, the academic performance and study habits of most students were at moderate level, which is not satisfactory considering the nature and importance of medical sciences. There was a significant relationship between study habits and academic achievement of students. Considering the important role of study habits in academic achievement and future careers of students, and since the majority of study habits can be taught and corrected, it is recommended that students’ study habits should be measured at the time of their entry to university, and during their studies, so they can receive training in order to learn or modify study habits. The present study was conducted on students of medical sciences. It is recommended that similar studies are conducted on students of other scientific fields. Conducting qualitative studies to examine the factors affecting students’ study skills and habits may also be beneficial.

Acknowledgments

This work was supported by the deputy of research and technology of KUMS (grant number 95306)]. The authors would like to thank the president and co-workers of deputy of research and technology of KUMS, and all the students who patiently participated in our study. We also extend our thanks to the clinical research development center of Imam Reza Hospital affiliated to KUMS for their kind help.

The authors report no conflicts of interest in this work.

Closing struggling schools helped student achievement in Denver, study finds

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The architects of Denver Public Schools’ former reform efforts are lauding a new study that validates a strategy that largely has been abandoned both in Denver and nationwide: closing low-performing schools and opening new ones that might serve students better.

The analysis from University of Colorado Denver researchers finds that most students who left closed Denver schools and attended new ones saw their test scores go up, with greater gains for English learners and students with disabilities.

Student achievement also went up districtwide, which study authors attribute to years-long efforts to give school leaders more autonomy, hold them accountable for results, and make it easier for families to choose among a range of schools.

“Too many school reforms in this country last for a year, and then the next year everybody changes their position based on what happened the year before,” U.S. Sen. Michael Bennet, Denver’s superintendent during the start of the reform era, said during a panel discussion Friday. “Denver, unlike many other places, had a commitment to a complicated and nuanced approach. I hope that people will have the chance to rediscover the work because of this research.”

Researchers who reviewed the study at Chalkbeat’s request said it was generally well-designed and makes a strong case that Denver’s approach contributed to improvements in student test scores. However, they cautioned that its boldest claim — that students experienced as much as three school years worth of additional learning — may be overstated.

The study adds to an extensive body of research on school closures , some of which has found mixed or negative effects. After years of bipartisan support from policymakers and others, test-based school accountability has mostly fallen out of favor in large urban districts.

In addition to the political backlash this approach frequently sparked , improvements stemming from it proved hard to sustain over time . But different approaches to school improvement have been slow to emerge as schools grapple with the pandemic’s effects on student outcomes .

Now, many urban districts — including Denver — are facing the prospect of school closures due at least in part to a different factor: declining enrollment. As it prepares to pick which schools will close next year, the Denver school board initially rejected the idea of considering academic performance but now says it can be a factor, just not the sole one .

Superintendent Alex Marrero tried to prevent the release of the student data used in the new study, contending that the researchers would ignore the downsides of reform policies and focus too narrowly on test scores. A spokesperson for the district did not respond to a request for comment on the study findings.

Denver schools study examines test data, graduation rates

Denver was once seen as a national exemplar of the so-called portfolio model , which encouraged school choice with an easy-to-navigate enrollment system.

The district also encouraged new schools to open, including charter schools, which are publicly funded but independently run, and innovation schools, which are district-run schools where principals have additional freedom and flexibility.

Simultaneously, the district closed schools with persistently low test scores.

Some of the Denver schools that opened during this time period continue to be sought-after and highly regarded schools. But others have closed due to low performance and low enrollment.

“It is really this idea that if you embrace the idea that choice is not a threat but an opportunity, if you don’t assume you have all the answers, and you hold schools accountable for results, you will see system-wide improvement,” said Parker Baxter, the study’s lead author and head of the Center for Education Policy Analysis at CU Denver’s School of Public Affairs. “And that is apparently exactly what happened in Denver.”

The new study isn’t the first to find that Denver made significant improvements during the reform era . In 2022, Baxter released a study that found that from 2007-2008 to 2018-2019, Denver students made an additional year or more worth of academic progress. Graduation rates also increased at a higher rate than they would have without the reforms, the study found.

But critics said that study, which used districtwide test data, didn’t account for the 20,000 new students Denver added during that time who were disproportionately whiter, more affluent, and more likely to do better on standardized tests.

The new study draws on test scores and other data from 40,000 individual students from Denver and 11 surrounding districts from the 2008-09 school year to the 2014-15 school year. The Denver students were matched demographically and academically with similar students in neighboring districts that did not embrace the portfolio model. The more time students attended Denver Public Schools, the greater the increase in their test scores compared with similar students, the study found.

The study also tracked individual Denver students over time, including those who attended schools that closed, those who attended new schools that opened during the study period, and those who attended schools targeted for district-led turnaround.

Most students who left a school that closed due to low performance for a new school that opened during this period saw their scores increase in math. Students who attended a new school saw test scores increase in math and English. One exception was Native American students, who generally saw their scores go down.

Students who attended schools in turnaround — an often demoralizing process that involved replacing the principal and many of the teachers — generally did worse.

“At least for the students in our sample, the most minimally disruptive interventions had negative effects for students,” Baxter said. “Arguably the most disruptive intervention had the most positive effects. It’s important to understand why.”

As the district prepares to close schools again, closing those with lower test scores could be a way to turn the disruption into academic gains, Baxter said.

Denver’s high school graduation rates increased dramatically during the time period of the study, but the same held true in many Colorado school districts . Overall, Denver students in the study were a little more likely to graduate high school but not more likely to go to college than their peers in neighboring districts.

Hispanic and English learner students in Denver were more likely to go to college than their suburban peers, while Denver’s Black students were less likely to enroll.

‘Strong evidence’ reforms were effective, but which reforms?

Douglas Harris, an economics professor at Tulane University who has studied school reforms extensively, said the latest study is “more convincing” than the first study that education reform policies influenced Denver student trajectories.

The new Denver study produced similar results to Harris’ own research in New Orleans, though students there saw more modest test score growth and greater effects on high school graduation and college-going rates, he said.

Rob Shand, an assistant professor of education policy and leadership at American University who wrote a critique of Baxter’s earlier work , said the new study addressed several concerns but may attribute too much of the improvements to reform policies.

Shand said the way the study authors added up yearly test score gains to arrive at large cumulative effects “might tend to overinflate the numbers.” Nonetheless, the study provides “strong evidence that the Denver reforms increased test scores quite considerably,” Harris said.

Baxter defended the approach and said it may even have underestimated the effects.

Baxter said nearly every policy in place in Denver at the time was related to education reform and the portfolio model, including paying teachers more to work in high-poverty schools , giving schools more money to serve students from low-income families, developing a customized school rating system , working closely with charter schools, and making it easy for families to choose among schools. That makes it reasonable to credit test score gains to the portfolio model more broadly, he said.

Shand said there’s value in studying comprehensive reforms, but it’s hard to know how to respond because it’s not clear which policies made the most difference. Still, in a time when education politics is increasingly polarized between defenders of traditional public schools and supporters of universal private school choice, Shand said the study results should give pause to both extremes.

“It really calls for a more balanced or measured approach,” he said.

At Friday’s panel discussion on the report, Bennet and former Denver Superintendent Tom Boasberg made a rare joint appearance to reflect both on the findings and on a political landscape that has changed a great deal.

Opponents of their reforms took control of the school board in 2019 and have been less friendly to charter schools and giving principals autonomy . DPS hasn’t closed a traditional school for low performance since 2016. In 2020, the board scrapped Denver’s school rating system and hasn’t come up with a replacement .

Bennet and Boasberg said the election of Donald Trump in 2016 polarized every area of politics and contributed to the erosion of a bipartisan consensus on education .

Boasberg, who now leads an American school in Singapore , said the study represents an opportunity to turn the focus from politics and rhetoric to policy and practice . He acknowledged, though, that the nature of the reforms also contributed to some of the backlash.

“These were very, very far reaching changes, and they changed the status quo in very deep and very profound ways,” Boasberg said. “And I think in any democracy, when you make very profound changes that change the status quo, there are people who are going to be unhappy and resist.”

Colorado bureau chief Melanie Asmar contributed reporting.

Erica Meltzer is Chalkbeat’s national editor based in Colorado. Contact Erica at [email protected] .

Denver has moved away from closing low-performing schools and opening new ones. Now, like many districts, it faces a new set of school closure decisions.

Applicants whose grants requests weren’t funded in August may get awards now.

The district is seeing increases in most student groups, including big bumps in the number of children learning English as a new language.

Denver no tiene suficientes estudiantes para llenar sus edificios, dijeron los representantes del distrito escolar.

New York City families can apply to more than 12 high schools this year, as well as any middle school across the city, the city’s Education Department announced.

Overall school attendance is improving, but children with disabilities and those from low-income families aren’t rebounding as well as their peers, the state reports.