research questions for study habits

The challenge of change: understanding the role of habits in university students’ self-regulated learning

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• Published: 10 April 2024

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• Louise David   ORCID: orcid.org/0000-0003-1973-4568 1 ,
• Felicitas Biwer   ORCID: orcid.org/0000-0003-4211-7234 1 ,
• Rik Crutzen   ORCID: orcid.org/0000-0002-3731-6610 2 &
• Anique de Bruin   ORCID: orcid.org/0000-0001-5178-0287 1  

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Study habits drive a large portion of how university students study. Some of these habits are not effective in fostering academic achievement. To support students in breaking old, ineffective habits and forming new, effective study habits, an in-depth understanding of what students’ study habits look like and how they are both formed and broken is needed. Therefore, in this study, we explored these aspects among first-year university students in six focus group discussions ( N  = 29). Using a thematic analysis approach, we clustered the data in five themes: Goals Matter , Balancing Perceived Efficiency and Effectiveness when Studying , Navigating Student Life: from Structured Routines to Self-Regulation Challenges , the Quest for Effective Habits with Trying to Break Free From the Screen as subtheme, and the Motivation Roller Coaster . Findings suggest that students had different study habits depending on their goals. Students had quite accurate metacognitive knowledge about effective learning strategies for long-term learning, but often used other learning strategies they deemed most efficient in reaching their goals. Students indicated intentions to change, but did not prioritize change as their current habits enabled them to pass exams and change was not perceived as adding value. Fluctuations in motivation and transitioning to a self-regulated life hampered students’ intentions to form new and break old habits. Next to insights into factors affecting students’ behavioral change intentions, the findings suggest the importance of aligning assessment methods with life-long learning and supporting students in their long-term academic goal setting to prioritize study habits which target lasting learning to optimally foster their self-regulated learning.

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Introduction

In higher education, students are required to plan, monitor, and execute their learning autonomously (Dresel et al., 2015 ; Zimmerman, 1986 ). Therefore, effective self-regulated learning (SRL), facilitated by the use of effective learning strategies, is essential for students’ academic achievement and lifelong learning (e.g., Dunlosky et al., 2013 ). However, many students struggle to use effective learning strategies optimal for long-term learning, such as practice testing, and often rely on passive strategies such as re-reading (Morehead et al., 2016 ; Rea et al., 2022 ). While training programs are successful in increasing students’ knowledge regarding these effective learning strategies, many students struggle to sustainably change their behavior and apply these learning strategies (Biwer et al., 2020a , b ; Foerst et al., 2017 ; Rea et al., 2022 ). This gap between students’ knowledge and behavior is partially due to students’ strong habits of using ineffective study strategies (Blasiman et al., 2017 ; Rea et al., 2022 ). However, so far, this gap between students’ knowledge and behavior and their study habits remained largely unexplored. To explore the gap between students’ knowledge and behavior further, we deem it essential to first gain a thorough understanding of students’ current study habits, how they usually form new, and break old habits.

Using a qualitative approach, we add to the current field of research by targeting an in-depth exploration of students’ study habits, which is currently lacking. Insight into these are essential to tailor educational strategies and training to better align with students' behaviors and needs. Awareness of potential struggles students might encounter when breaking old or forming new habits provides important insights into hurdles students face when attempting to modify their study behavior and how they can be supported in achieving their goals.

Self-regulated learning in higher education

In higher education, learning is happening mostly in teacher-absent environments, which requires students to effectively self-regulate their learning (Dresel et al., 2015 ). However, many students struggle to self-regulate effectively. They monitor and control their learning inaccurately, which has a negative impact on their academic achievement (Hartwig & Dunlosky, 2012 ). One way of fostering self-regulated learning is by helping students to use learning strategies which are optimal for long-term learning (e.g., “desirably difficult” learning strategies, Bjork & Bjork, 2011 ). Examples of desirably difficult learning strategies are practice testing, interleaving items of various categories, and spacing learning sessions over time (Dunlosky et al., 2013 ). A shared commonality of these effective strategies is that they require an active learning process with repeated memory retrieval of information (Bjork & Bjork, 2011 ).

While essential for self-regulated learning, students often avoid desirable difficulties or fail to use them in the long-run, even when being aware of their benefits (Biwer et al., 2020a , b ; Rea et al., 2022 ). One reason for not using effective learning strategies is that students often have strong habits of using surface processing strategies. Instead of using desirable difficulties, students rely on passive learning strategies and mass their study sessions close to the exam instead of spacing the sessions over time (Blasiman et al., 2017 ; Dembo & Seli, 2004 ; Foerst et al., 2017 ). Often students start using these strategies in high school already (Dirkx et al., 2019 ).

Next to struggling to use effective learning strategies, students often face additional regulation issues during their self-study. Learners also need to employ resource management strategies such as effort and motivation management to optimize learning conditions (Dresel et al., 2015 ) by, for example, planning their study sessions or asking for help if necessary. While resource management strategies have been identified as an essential factor for academic performance (Grunschel et al., 2016 ; Waldeyer et al., 2020 ), many students struggle with time management (Basila, 2014 ; Thibodeaux et al., 2017 ) and encounter motivational problems leading to for example procrastination (Grunschel et al., 2016 ).

Metacognition and resource-management strategies are often indicated as important factors in self-regulated learning models (for an overview, see Panadero, 2017 ). However, these factors might not fully explain how students maintain recurring study behaviors over the long term (Fiorella, 2020 ). Instead, habits, which, once formed, are usually not guided by conscious intentions and goals, have been suggested crucial for academic behaviors that need to be repeated consistently over an extended period (Fiorella, 2020 ). Therefore, to foster students’ self-regulated learning, it has been suggested to support students in building new study habits, which, for example, incorporate desirable difficult learning strategies (Fiorella, 2020 ).

Behavioral change and study habits

In the last years, interventions have been developed to enhance students’ knowledge and initial use of effective learning strategies (e.g., Ariel & Karpicke, 2018 ; Biwer et al., 2020b ; Broeren et al., 2021 ). While showing positive effects, the actual transition of this knowledge and application to students’ self-study in the long run remain limited (Dignath & Veenman, 2021 ). The majority of these interventions focus more on increasing students’ knowledge and less on building new habits or changing the actual study behavior consistently potentially explaining the limited application. Habits, however, are an important predictor of behavior in addition to, for example, attitudinal and control beliefs (Verhoeven et al., 2012 ; Verplanken, 2018 ), and are seen as a key factor in behavior maintenance (Rothman et al., 2009 ). To ultimately support students in actually applying effective learning strategies in the long run, it is essential to first understand the factor that drives most behavior: habits (Rothman et al., 2009 ; Verplanken, 2018 ).

Habits are behaviors that reoccur in stable contexts. Once a habit forms, behavior is led by automatic, effortless actions instead of deliberate intentions (Gardner, 2015 ; Lally, et al., 2010 ). According to our conceptualization, study habits can relate to behaviors such as the usual length of a student’s study session, learning strategies used, or study timing and environment. Study habits can play an essential role in harming or helping students to achieve long-term academic goals. Irrespective of whether these habits help or hinder goal achievement, they initiate behavior automatically and effortlessly. Habits usually form when an association between a certain behavior and context is established by consistently repeating a behavior in that context (Gardner, 2015 ; Lally & Gardner, 2013 ). Due to the association, the habitual behavior is automatically and sometimes unconsciously activated (Aarts & Dijksterhuis, 2000 ) while alternative behaviors become less accessible (Danner et al., 2007 ). Often, the effort required to initiate the habitual behavior decreases over time and initiation becomes effortless (Lally et al., 2011 ). Even when intentions change, engagement in habitual behavior commonly persists (Adriaanse & Verhoeven, 2018 ).

According to the goal–habit interface model (Wood & Rünger, 2016 ), many habits are initiated by goal-directed behavior. Initially, before habit formation, goals drive individuals to repeat a certain action in a specific context. Once a habit is formed, the habitual behavior shifts from goal-dependent to goal-independent behavior. In this case, behaviors are enacted based on context cues and irrespective of goals (Mazar & Wood, 2018 ). Nevertheless, as many individuals are unaware of this habit formation process, they might misattribute their habitual behavior to goals or intentions instead of habits (Loersch & Payne, 2011 ; Mazar & Wood, 2018 ).Wood & Neal ( 2016 ) suggest various essential components for habit-based interventions that target initiation and maintenance of health behavior change. They suggest the importance of habit-forming approaches for fostering repeated engagement in healthy behaviors while also disrupting undesirable behavior by habit-breaking approaches. As main components for habit formation, they suggest frequent repetition of the desirable behavior, creating a re-occurring context and context-cues, and administering rewards randomly (Wood & Neal, 2016 ). To break undesirable habits, context-cue disruption, re-structuring of one’s environment, and monitoring one’s behavior are suggested as efficient (Wood & Neal, 2016 ).

While there has been quite some research showing the beneficial effects of habits in health behavior change (e.g., exercising habit, healthy eating habit), only a few studies have focused on how study habits could improve students’ study behavior (e.g., Galla & Duckworth, 2015 ). Students’ ineffective study habits such as ineffective learning strategy use (Biwer et al., 2020a , b ; Foerst et al., 2017 ; Rea et al., 2022 ), high smartphone use (Chen & Yan, 2016 ; Lepp et al., 2015 ), or poor time management (Basila, 2014 ; Thibodeaux et al., 2017 ) seem to play a role in their study behavior and academic achievement. Breaking these ineffective habits and forming effective study habits instead by, for example, incorporating more desirably difficult learning strategies could help students to optimize their self-regulated learning and academic achievement.

In the present study, we aim to gain a better understanding of the nature of university students’ study habits, how students usually form new habits, and how they (try) to break ineffective habits. We explored this using a qualitative approach via focus group discussions with first- and second-year university students. As our goal was to dive beyond surface-level observations and gain an in-depth understanding of students’ experiences rather than generalizing to a larger population, a qualitative approach seemed most appropriate (Morse, 2008 ). Compared to a quantitative approach, a qualitative approach via focus groups or interviews offers various benefits (for a more general overview of focus group discussions in medical education, see Stalmeijer et al., 2014 ). First, they offer a relatively time- and cost-effective access to students’ thoughts and experiences. Second, by being able to directly engage with students, it is possible to ask students for further elaboration or clarification, which would not be possible using for example questionnaires and therefore ensuring an in-depth understanding. Third, due to the flexibility of this approach and our semi-structured question guide, we were able to capture students’ opinions while limiting imposing pre-existing assumptions about their study habits. Most importantly though, we anticipated that the interactions between students would be essential when discussing study habits and focus group discussions would thus allow a more diverse and multifaceted picture of students’ study habits. While habitual behaviors could be unconscious, we expected that hearing other students’ experiences would facilitate students’ reflections on similar or dissimilar experiences. Insights from our study can help to inform potential future study habit interventions to overcome students’ knowledge-behavior gap.

Research setting

This study was conducted at the Faculty of Health, Medicine, and Life Sciences (FHML) at Maastricht University, which is a public research university in the Netherlands. At Maastricht University (UM), the academic year is divided into six different blocks (i.e., teaching periods), including different thematic courses lasting between 4 and 8 weeks. Courses usually consist of lectures and tutorial sessions and are finalized with an exam. The tutorial sessions are structured according to the problem-based learning (PBL) approach. Within this approach, authentic scenarios are central to learning (Dolmans et al., 2005 ). In small tutorial groups, ranging from 10 to 12 students and one tutor, students are introduced to these scenarios according to a seven-step model (Moust et al., 2005 ). The first five steps, (1) term clarification, (2) problem definition, (3) brainstorming explanations, (4) structuring and analyzing the identified explanations, and (5) formulation of learning goals, take place during the tutorial session. Students then individually study literature to answer their learning goals during (6) self-study. Lastly, during a next tutorial session, students integrate and discuss findings from their self-study in a (7) post-discussion.

Admission to the medical program at UM is a selective procedure, with only limited places available. Students are only eligible if having followed a certain combination of STEM courses during high school. Furthermore, potential candidates have to undergo two selection rounds. In the first selection round, students’ high school transcripts, curriculum vitae, and a written assignment are evaluated. If of sufficient quality, candidates are invited to a second selection round, which is an assessment day at the university, where potential candidates have to fulfill various assignments during which their cognitive and (inter)personal characteristics and skills are assessed. Based on these criteria, students are ranked and selected. Admission to the biomedical program at UM was not selective for the cohort participating in this study. The only eligibility criterion was that students had followed a certain combination of STEM courses during high school and were proficient enough in English.

The majority of first-year FHML students at UM are assigned to a mentor and receive a formal learning strategy training in their first weeks (“Study Smart”; Biwer & De Bruin, 2023 ) to support their self-regulated learning and professional development. The learning strategy training consists of three 90-min small-group training sessions with different goals. In the first session, the main goal is to increase students’ awareness about effective and ineffective learning strategies, why certain strategies work better, and possibly misleading experiences that students might encounter when using (in)effective learning strategies. During the second session, students are asked to try-out different effective learning strategies and think about a concrete plan, how they could incorporate these during their self-regulated learning. During the third session, which is held a few weeks after the previous sessions, students are asked to reflect on their learning strategy use during their self-regulated learning and how they could improve. Throughout the year, students meet with their mentor and write a portfolio reflecting on their competencies related to program content, professional- and study behavior.

Participants

Twenty-nine first- and second-year medicine ( n  = 14) and biomedical sciences ( n  = 15) bachelor students participated in one of six focus group discussions. Students were on average 20.1 years old (14% male). Students were recruited via multiple channels. The first author contacted the mentor and course coordinators of the respective bachelor programs to share the study information with their students. Additionally, students were recruited via posters and approached after tutorials and lectures. During the recruitment phase, the study goal was advertised as exploration of students’ study methods and habits. We obtained written informed consent from all participants prior to the study. Participants completed a demographic questionnaire inquiring about their age, study program and year, and grade point average (GPA). Students’ GPA ranged from 5.8 to 9, with the mean GPA being 7.4 (on a scale from 1 to 10, with 10 being the highest). Two students did not indicate their GPA. The faculty’s ethical review board (FHML-REC/2022/049) approved the study. Students received a small monetary reimbursement to compensate for their participation.

Focus groups

Students who completed the demographic questionnaire and indicated their availability were invited to the focus group discussions at university. The focus groups lasted approximately 80 min ( M  = 78.4 min, SD  = 4.2 min) and were moderated and observed by the first and second author. Based on a semi-structured focus group guide (see supplementary materials), students were asked which study methods they usually used during their self-study, what a typical study day looked like, and about their experiences with forming and breaking habits. The clarity of the questions within the focus group guide was piloted with two students prior to the focus group discussions. Based on their feedback, the wording of the questions was slightly adjusted to improve clarity. The first four focus groups were held at the end of students’ first academic year. Two additional focus groups were held at the beginning of students’ second bachelor year. The focus group guide was adjusted before the second part of data collection as we noticed that students had difficulties reflecting in-depth on their experiences with forming and breaking habits. Therefore, we created three vignettes describing concrete examples of how a habit was broken or formed based on students’ reflections during the first focus groups. Data was collected iteratively and occurred simultaneously with data analysis. In line with Morse ( 2015 ), as soon as we estimated our data to be sufficiently rich to gain a deep understanding of students’ study experiences and their habit-breaking and habit-forming experiences, we determined data saturation and stopped data collection. Data saturation is commonly an interpretive judgment in thematic analysis (for a critical stance regarding the concept “data saturation,” see Braun & Clarke, 2019 ). In our case, we started data analysis by descriptive line-by-line coding of the so far collected transcripts, clustering these codes, and searching for patterns, simultaneously to data collection. Based on the understanding we gained during these first analytic steps, we determined to have collected sufficient data to understand students’ experiences after six focus groups.

Data analysis and coding procedure

All focus groups were audio recorded and transcribed verbatim. Based on the thematic analysis approach (Braun & Clarke, 2006 ), we analyzed the focus group discussions inductively. Our analysis was data-driven and thus, the theme development did not mirror our question guide nor do the themes fully align with our potential pre-existing assumptions about students’ study habits (Braun & Clarke, 2006 ; Kiger & Varpio, 2020 ). We used pre-existing theories to establish our focus group guide and kept this knowledge as sensitizing concepts during the coding procedure (Bowen, 2006 ). We conducted a semantic analysis of participants’ accounts by interpreting their explicit meanings as recorded and transcribed. After thoroughly listening to the audio recordings and reading the transcripts in-depth multiple times, they were descriptively coded line-by-line using Atlas.ti (version 23.0.7.) by the first author (an extract of our codebook is included in the supplementary materials). Using these descriptive codes, the second author coded 50% of two transcripts without insights into the first coder’s line-by-line coding. The outcomes and coding alignments of these partial transcripts were discussed and definitions of codes were further specified, if necessary. Then, patterns within and across focus groups were discussed within the whole research team based on summaries of the transcripts and clustering of the descriptive codes done by the first and second author. Based on this discussion, the first and second author formulated themes, which were reviewed and refined with the entire research team. Additionally, the formulated themes were checked against the coded data and original transcripts. Throughout the analytic procedure, our research team engaged in regular discussions and asked for feedback from scholars outside of the research team during roundtable sessions and conference presentations to critically examine interpretations and findings. We followed a pragmatist approach in analyzing the data, prioritizing the practical relevance of knowledge instead of attempting to explain “reality” (Cherryholmes, 1992 ). The pragmatist approach offered us the flexibility and adaptability of addressing our research questions as well as generating practical implications from the identified themes while interpreting the data within our specific context.

Reflexivity statement

LD is a PhD student who completed a Bachelor’s degree at Maastricht University and is therefore familiar with the UM system also from a student perspective. FB is an educational psychologist with research interests in self-regulated learning and teacher professionalization and knows the PBL system in their role as mentor and tutor. RC is a cognitive psychologist with research expertise in behavior change and technology. AdB is an educational psychologist with research expertise in self-regulated learning in higher education. RC and AdB know the PBL system in various roles (student, teacher, mentor). We are aware that the findings of this study are co-created by interactions between the authors and participants. We thoroughly discussed each process step with all team members and discussed intermediate findings with educational scientists outside of the team and continuously reflected on the extent to which our individual personal experiences and beliefs shaped the research project.

We clustered students’ experiences into five themes: Goals Matter , Balancing Perceived Efficiency and Effectiveness when Studying , Navigating Student Life: from Structured Routines to Self-Regulation Challenges , the Quest for Effective Habits with Trying to Break Free From the Screen as subtheme, and the Motivation Roller Coaster .

Goals matter

Students mentioned various goals, which influenced their study behavior. Many students had a clear short-term goal of passing the exam in mind. For them, studying during the course served the goal of “collecting all the information” (student studying medicine (MED), focus group (FG) 2) to prepare for tutorial sessions. Studying for the exam served the goal of “actual studying” (student studying biomedical sciences (BMS), FG2), during which information is memorized or learned. Students experienced more pressure when studying for an exam compared to studying during the course. Approximately 1.5 weeks before an exam, students started intense studying. During this period, they dedicated extensive time to studying, often sacrificing a work-life balance and reducing time for activities like exercising, socializing, and hobbies.

Other students indicated having clear long-term academic goals such as receiving a high GPA or wanting to become a good doctor. These clear long-term goals helped them to study consistently, be less exam-oriented, and prioritize their studying also during the course, even if having to sacrifice other activities. Instead of studying solely to pass exams, students explained to be more consistent in their study behavior and tried to understand and learn the content continuously. They mentioned achieving this by planning and spreading their study load throughout the course. For example, one student mentioned:

I don’t study for exams anymore, I study because I want to be a good doctor. And I think that mindset also helped me change. […]. So it’s harder to find time around [studying], but I also prioritise [studying], university is the most important thing for me. If it means I don’t go to a party or I don’t go to the gym, which I also want to do, then that’s just how it is. (Student MED, FG5)

Balancing perceived efficiency and effectiveness when studying

Students generally had quite accurate metacognitive knowledge and were aware that active learning strategies and distributed learning sessions were more effective for long-term learning. Contrastingly, students did not necessarily use those strategies as they experienced that their own study strategies “work” (multiple students in multiple FGs) and were most efficient in reaching their short-term goal to pass the exam or having a strong habit of using them. For example, one student mentioned:

Well, I know it’s not really useful. But I still [summarize] a lot. But I know that it’s […] been proved that it’s not really effective. But I still, I don’t know, it’s just a habit. […] And it works. (Student MED, FG 3)

Students differed in which strategies they deemed to “work” (multiple students in multiple FGs) for themselves. For tutorial preparations, students usually read and summarized the provided sources. For exam preparations, students used various active and passive learning strategies such as re-reading, summarizing, creating mind maps, watching videos, recalling information, testing themselves by using past exams or creating flashcards, and explaining content to others or themselves. The amount of practice testing students used during their self-study depended on the availability of past exam questions in their study program as students experience creating practice questions themselves as too time consuming:

Some of our professors, they made […] really extensive kind of quizzes with lots of questions. And that was really helpful. I wish they did that for everything. (Student BMS, FG6)

To optimize their study efficiency, next to using cognitive learning strategies, students tried various resource management strategies, such as creating a planning for their tasks or studying with friends to stay motivated but often faced challenges in accurately managing their time and effort. Students usually started their study session by creating a planning or to-do list, but it was difficult to accurately know how long a task would take or to “really stick to it” (Student BMS, FG3). Instead of studying until a certain time, students usually studied until the task was finished or they could not focus anymore.

Navigating student life: from structured routines to self-regulation challenges

Students reported basing their study habits on what they had learned during high school, despite university being experienced as different. Next to the content being perceived as more in volume and difficulty, students also mentioned having to adjust to the change of setting. During high school, students often had a structured daily routine. When transitioning to university, they had to adjust to the lack of structure and external control, but also higher flexibility associated with student life. While students appreciated this increased freedom, it also came with the challenge of managing themselves and self-regulating various aspects of life: starting to study, moving to a new city, looking for new hobbies and friends, or managing their household.

When I lived with my parents in high school […], you have like a whole routine. […]. Now you can do things whenever you want to do it. And […] sometimes you have parties on Monday or on Wednesdays. So, it’s on random days. Yeah. And then you’re tired on Tuesdays. So, then you don’t do as much as other days. […] I think, it’s also part of student life. (Student MED, FG2)

Some students solved the lack of structure by actively creating more external structure in their daily life by joining committees, making appointments with others, or creating a clear separation between work and “personal” life. For other students, the lack of external structure seemed to negatively influence their willingness to form habits as they experienced habits as restricting flexibility. Some students appreciated the flexibility that they associated with student life and did not report actively looking for more structure. In search for more structure, students differed in their habit and preference of study location. Some students preferred to study at home to avoid distractions, whereas others preferred to study at university as they found it easier to initiate studying with others around and appreciated a separation between their studying and living space. During courses, students were more flexible in their study setting.

The quest for effective habits

Even though students experienced their current strategies to “work” for the exam, they reported intentions to change their current study behavior. These intentions targeted improving time management, such as following their planning, procrastinating less, cramming less, limiting screen time, and changing their sleeping schedule. They mentioned making study appointments with others, which helped to feel more accountable, and promoted adherence to intended behavior. Students also mentioned wanting to add steps to their current study habits such as completing their study notes or creating flashcards after each tutorial. For example, a student mentioned “I first had to […] talk about this topic, answer the question, then I was allowed, for example, to go to the bathroom” (student BMS, FG4) or working through flashcards when traveling. While students had intentions to change, they mentioned not necessarily prioritizing working on realizing their intentions since their current habits were sufficient to pass their exams but also encountering difficulties when trying to realize them. Students identified various reasons for this, for example, difficulties in creating a feasible planning, following their intention when not being motivated, or falling back into old habits when experiencing a setback. While having good intentions, students perceived change to be effortful, time-consuming, or being insecure about whether a change would actually lead to an improved outcome. For example, one student mentioned:

It’s not enough to have motivation to change that one point. Because it’s what you say, how do you make the change? By doing it daily. […]. That’s, you know, what I’m trying to do. Like be more consistent. […]. I’ll do great for the first couple of days, maybe two weeks, if I was really motivated. But then after I wake up on a bad day, I really don’t feel like it. And it’s this boring topic. I’ll push it back. […]. I’ll do something else. Then time runs out. Then we’re already kind of back in the bad cycle of procrastinating on everything. […] If there’s not the stress of a deadline, then it comes down purely to motivation every day. (Student BMS, FG3)

Trying to break free from the screen

One particularly challenging habit students tried to break was their smartphone habit. Students mentioned turning to their phones or study unrelated websites automatically when lacking focus or procrastinating. This was experienced as distracting and negatively influencing students’ studying. They tended to spend more time on their phone than anticipated, for example, if wanting to briefly check something. To reduce this automatic use, students tried to discontinue their habit by re-structuring their environment so that the distraction would be less accessible or interchanging their phone use with another activity such as reading. Instead of having their phone on the table when studying, they put their phone out of sight, blocked or deleted apps in the morning, or exchanged their phone with a friend’s phone. Even though students used various strategies to reduce the distraction from these devices, students continuously struggled in limiting their screen time.

I am so done with my phone being the hugest distraction in my life at this point, it just annoys the hell out of me. I’m actually breaking a habit right now, it’s called ‘no Instagram anymore’. Yes, it’s very bad, but I am... I’m not going to say I am improving because I am not, but I am trying to improve. (Student BMS, FG6)

The motivation roller coaster

Students described experiencing a fluctuation in motivation throughout a course and academic year, which influenced their study behavior and behavioral change intentions. With their past stressful exam preparation in mind, students reported beginning a new course with many resolutions wanting to improve what went “wrong,” such as aiming to study more consistently or to start exam preparations earlier. Students often managed to realize their resolutions for the first few weeks of a new course. However, after approximately 2 weeks, students lost motivation and started to slack with their studying (e.g., studying less consistently). They experienced less pressure to study, and thus experienced more motivational conflict when initiating studying due to tempting alternative activities, other course obligations, or interferences outside of university. For example, one student, being well aware of the consequences of procrastination, mentioned:

I can relax now and do this fun thing. And then maybe have to do like, a quick version of this assignment late at night. (Student BMS, FG3)

Three weeks prior to the exam, students felt increased pressure when realizing how close the exam and how much work was left. This pressure motivated students to catch up on the coursework and spend more time studying. Often, students focused on getting the studying done (e.g., creating summaries for each case) and cramming the content using methods that previously worked to pass the exam. For example, one student mentioned:

I’m also motivated in the beginning of a new block. […] I have this motivation over me. Like, well, now I’m going to keep up with it. And then sometimes, […] I lose track of the course that we’re in. And I’m behind again. And then I lose it a bit. So, when I get behind, and I’m like, okay, now I just do the minimal. And then two, a week and a half, before the exam, then I get my motivation back. (Student MED, FG2)

This paper outlines the findings of a study exploring university students’ study habits during self-regulated learning. We held focus groups aiming to explore university students’ current study habits, habit formation, and experiences with breaking habits. A thematic analysis of the transcribed data revealed five themes and one subtheme, which offer insights into our research aims regarding how students usually form new habits, and how they (try) to break ineffective habits. Our study offers a detailed exploration of university students’ study habits. Using a qualitative approach, we were able to dive beyond surface-level observations by exploring students’ experiences and factors, which influence these habits, their formation, and the challenges associated with breaking habits in-depth. While our chosen approach allows for a rich and nuanced understanding of the multifaceted nature of students’ study habits, the goal of a qualitative approach is commonly not to generalize findings to a larger population (Morse, 2008 ). The findings of this study are experiences from a specific student population rooted within a specific educational and cultural context. Including a thick description of this context, we try to establish transferability of our findings by indicating how they could apply to other contexts and student populations.

Students’ study habits

Students had different study habits depending on their goals. Students with clear short-term goals of passing the exam focused on collecting information during the course and started intense studying shortly before the exam. Students with long-term academic or career goals planned their study sessions continuously and focused more on learning the study content. Students differed in their preferred study setting when preparing for exams, but usually had a habit and preference of where and how to study. During courses, students were more flexible in their study setting. These findings suggest that long-term academic goal setting helps students to prioritize long-term learning by spreading out study sessions and focusing on learning the study content continuously. Long-term academic goal setting might be more evident for some study programs than for others. In study programs such as medicine, many first-year students have a clear goal of becoming a good doctor with long-term retention of knowledge and skills as important factors to reach that goal. Study programs with more diverse career paths might make it difficult for students to envision clear long-term goals. This lack of long-term goal setting might hamper students’ motivation to ensure more effortful studying in a manner that ensures long-term retention or best possible grades. Previous research indicates that students’ long-term perspectives are related to better self-regulation strategies (Bembenutty & Karabenick, 2004 ; De Bilde et al., 2011 ).

Students tried to be strategic in their learning strategy use by balancing perceived efficiency and effectiveness of the methods in reaching their goals. For tutorial preparations, students usually read and summarized the provided sources. For exam preparations, students combined active and passive learning strategies such as summarizing, watching videos, or explaining content to themselves. Unlike often assumed in the literature (e.g., Morehead et al., 2016 ; Yan et al., 2016 ), students in the current sample had quite accurate metacognitive knowledge. This could be related to the fact that they followed a formal learning strategy training at the beginning of their studies or the PBL system employed at UM, which aims to foster an active learning approach (Dolmans et al., 2005 ). Students might have been aware of effective and ineffective learning strategies and received suggestions on how to incorporate as many active learning approaches as possible within their self-regulated learning. Nevertheless, they used learning strategies, which are not the most effective for long-term learning but ones that they deemed most time-efficient to pass exams. While students were often aware of this discrepancy, assessment forms were an important driver for learning strategy choices. This is in line with prior research indicating that students adapt their learning strategies to examination requirements (Broekkamp & Van Hout-Wolters, 2007 ; Rovers et al., 2018 ). Bachelor students are often assessed using multiple choice questions, which focus on recognizing information instead of retention. They thus use learning strategies to maximize success for that assessment type. In order to nudge students to use learning strategies essential for long-term learning, it is crucial to align assessment by using methods that stimulate long-term learning and prioritize testing understanding instead of recognition (Van der Vleuten et al., 2010 ).

Furthermore, students’ willingness to incorporate active learning strategies such as retrieval practice seemed dependent on the available resources in their study program. In the medicine program, students had access to past exam questions and thus used them during exam preparations. Students in the biomedical sciences program, having no access to previous exam questions, found it difficult and time-consuming to create practice questions themselves and appreciated course coordinators who provided example questions. This suggests that more support from educators, such as providing practice questions or training sessions on formulating practice questions, might further increase students’ use of active learning strategies.

Forming and breaking habits

In line with previous research, students reported basing their study methods on what they had learned during high school (Dirkx et al., 2019 ). They updated these methods if they did not help them to achieve their goals by trying to embed additional steps in pre-existing habits (e.g., if going to bed, then reading notes). This method of specific if–then plans also called implementation intentions (Adriaanse & Verhoeven, 2018 ; Gollwitzer, 1993 ) is commonly suggested to foster habit formation and habit breaking. By pre-selecting a situation and mentally rehearsing the if–then link, individuals are more likely to automatically trigger the desired behavior when encountering the situation. Formulating these if–then plans could create new associations that compete with existing habits. If the new cue-action link is stronger than the habitual pattern, the desired action could potentially override the habitual response. While research across various domains supports the effectiveness of implementation intentions in promoting goal-directed actions (Adriaanse et al., 2011 ; Gollwitzer & Sheeran, 2006 ), it is unclear whether implementation intentions influence learners’ learning outcomes or metacognition (Hoch et al., 2020 ).

Students reported intentions to change their study behavior. While their intentions targeted mainly improving time management aspects or wanting to add steps to their current study habits, disentangling the extent to which students wanted to realize these intentions was difficult. Additionally, detailed reflections of how students broke past ineffective habits and whether they actually changed their behavior once their habits did not “work” anymore remained scarce, making it difficult to fully target our third research aim. Students did not see change as a priority because their current method “worked” to pass exams. As mentioned above, assessment was an important driver for students’ learning strategy choices but also a key factor in their behavioral change intentions. Students were successful in passing exams and thus did not perceive change as necessity or added benefit. However, they also indicated not knowing how to change, or experiencing change as effortful and time-consuming. The difference between not changing because perceiving change as having no additional value or because not knowing how to has important implications for behavioral change interventions. Students who do not perceive change as beneficial might profit from interventions that highlight the utility value of effective learning strategies (e.g., McDaniel & Einstein, 2020 ) in achieving a sufficient grade to pass a course as efficiently as possible. Students who do not know how to change might profit from interventions that provide them with information on how behavioral change could be achieved. More research is necessary to disentangle the extent to which students are willing to form new and break old habits and if so, how they could be best supported in this.

Another factor influencing students’ intention to change and breaking old habits was their fluctuating motivation throughout the course. Students began a new course with many resolutions wanting to improve what went “wrong” the block before but motivational conflict and their usual context quickly disabled them from realizing their intentions and instead continuing with unwanted behavior. In line with Verplanken and colleagues ( 2018 ), this finding suggests a potential importance of temporal considerations in behavioral change interventions in transition periods. Interventions held at the beginning of a new course might benefit from students’ increased motivation to change.

Additionally, students’ capacity to form new and break old habits seems to be influenced by their transition to a more independent environment. During this transition, they did not solely focus on establishing effective study habits but also had to navigate their flexible schedule during which they encountered other self-regulation challenges. According to the habit discontinuity hypothesis (Verplanken & Wood, 2006 ), major life events or disruptions can serve as catalysts for behavior change, indicating that the transition to university could potentially serve as a great opportunity to break existing habits and form more adaptive ones. As the transitions create a habit discontinuity, people change their habits and adopt new behaviors as old cues and routines that support existing habits are weakened or disrupted (Verplanken et al, 2018 ). As a result, individuals are more receptive to new opportunities to establish new habits or modify existing ones. This suggests that it might be valuable to support students in building effective habits as soon as they start university to make use of the discontinuity of existing habits, or, as mentioned above, at the beginning of a new course later in the semester. Contrastingly, our findings suggest that the new context and flexibility also challenge the formation of new habits, since it is difficult to “piggy-bag” new habits onto existing ones and because the needs for what makes learning effective to pass exams in the new context are not clear yet. Students solved this by actively looking for more structure. More research is necessary to investigate how the transition to university influences students’ capacity to form new habits.

Another factor, which could be important in students’ study habits and breaking and formation hereof, is co-regulation. The latter describes how learners’ cognition, emotions, and motivation during learning are influenced by interaction with others (Bransen et al., 2022 ; Hadwin & Oshige, 2011 ). Students mentioned making study appointments with others, which helped them to feel more accountable for their actions and thus promoted adherence to their intended behavior, suggesting that co-regulation could be an important factor in supporting students to break ineffective habits and form new habits. Furthermore, by observing how peers study, students could learn to  model adaptive behavior, enabling them to form habits that incorporate more effective learning strategies. Furthermore, being able to exchange experiences with peers during the habit formation and breaking process, which might be associated with negative emotions such as stress and frustration, could help students to cope and stay motivated during their behavior change journey. However, more research is necessary to investigate how co-regulation could influence students’ study habits.

Strengths and limitations

Our findings highlight the central role of students’ goals in shaping their study habits. Knowing how goals influence study habits offers valuable insights into the importance of tailoring educational strategies to better align with students’ goals and to shed light onto goal-driven behavior in education. Furthermore, the discrepancy between students’ knowledge and behavior when it comes to the limited application of effective learning strategies seems to stem from the low perceived efficiency of these strategies, highlighting a need to increase students’ perceived efficiency of effective learning strategies to close the gap between knowledge and behavior. Furthermore, the identified challenges related to motivation fluctuations within and throughout a course and the transitioning from high school to a self-regulated learning environment in university present original perspectives, which so far remain underexamined in the context of self-regulated learning. Our study offers valuable insights into the dynamic hurdles that students face when attempting to modify their study habits and highlights the importance of aligning assessment methods with life-long learning goals. However, this study has various limitations. First, we conducted convenience sampling. We did not target a specific target population but all first-year biomedical sciences and medicine students were eligible to participate. As the study goal was advertised as an exploration of students’ study methods and habits, it might have been possible that especially students who were more confident in their study methods or habits participated leading to a biased perspective. While we cannot rule this out, students were openly sharing that they engaged in methods that they thought were not the most effective and also mention not currently wanting to change their habits. Furthermore, students’ self-reported GPA ranged from 5.8 to 9, suggesting a mix between low- and high-achieving students. Additionally, the students’ in our sample received a formal learning strategy training in their first weeks to support their self-regulated learning and professional development, which potentially shaped their study behaviors and perspectives and thus outcomes of this study. Next to this, we did not split students from the two different study programs but mixed them within our focus groups. As mentioned above, the structure of the study programs might have shaped the results and further research is necessary to investigate to what extent these findings transfer to other study programs. Second, we held four focus groups at the end of students’ first academic year and two focus groups at the beginning of students’ second academic year. This change in context might have influenced students’ perspectives on their study methods and habits. Future research is necessary to investigate to what extent students’ study methods and habits change throughout their study program. Third, we asked students to reflect on their habitual behavior. As habits are often unconscious, we did not explicitly ask students about their habits but instead asked them to reflect on behavior they usually engaged in. The fact that we did not offer any definition of what counts as a usual behavior might have led to different interpretations hereof. While not the goal of this study, a quantitative research design capturing students’ habitual behavior could give more systematic insights by clearly defining and operationalizing the concepts of “usual behavior” in measurable terms. For example, it could be operationalized as behaviors that participants engage in at least three times a week or behaviors that they have engaged in consistently for the past six months or using the Self-Report Habit Index (SRHI, Verplanken & Orbell, 2003 ).

Overall, this study contributes to the literature by providing a qualitative exploration of university students’ study habits, formation hereof, and difficulties they experience when breaking habits. A thematic analysis of six focus groups indicated that students had different study habits depending on their goals. While showing accurate metacognitive knowledge of what are effective learning strategies, students often used other learning strategies they deemed most efficient in reaching their goals. Students indicated intentions to change but did not prioritize change as their current habits enabled them to pass exams and change was not perceived as adding value. Fluctuations in motivation across courses and transitioning to a self-regulated life hampered students’ intentions to form new and break old habits. The findings give insights into influential factors affecting students’ behavioral change intentions and suggest the importance of aligning assessment methods with life-long learning and supporting students in their long-term academic goal setting to prioritize study habits that target lasting learning to optimally foster students’ self-regulated learning.

Data Availability

Due to the nature of the research, supporting data is not available to ensure privacy of participants.

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Acknowledgements

We thank our participants for their time-commitment and sharing their experiences openly. Additionally, we would like to thank the members of the EARLI Emerging Field Group 3 “Monitoring and Regulation of Effort” for the ongoing discussions on the topic of effort monitoring and regulation that contributed to this research.

This work was funded by the Dutch Research Council (NWO) (VIDI grant number VI.Vidi.195.135) awarded to Anique de Bruin.

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All authors contributed to the study concept and design. Material preparation, data collection, and analysis were performed by LD and FB in close consultation with AdB and RC. The first draft of the manuscript was written by LD. All authors commented on previous versions of the manuscript and read and approved the manuscript.

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David, L., Biwer, F., Crutzen, R. et al. The challenge of change: understanding the role of habits in university students’ self-regulated learning. High Educ (2024). https://doi.org/10.1007/s10734-024-01199-w

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THE IMPACT OF STUDY HABITS ON THE ACADEMIC PERFORMANCE OF STUDENTS

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ariel ochea

Impact Factor(JCC): 1.7843-This article can be downloaded from www.impactjournals.us ABSTRACT The development of a Country relies mostly on the levels of education among the people. Without education human race would have remained but as another animal race. Education is a process towards development. The term study habit can be as the students' way of study whether systematic, efficient or inefficient. Academic achievement refers to what and how an individual has learnt qualitatively and quantitatively after a period of instruction given. A habit is something that is done on a scheduled, regular, planned basis and that is not relegated to a second place or optional place in one's life. It is simply done, no reservations, no excuses, and no expectations. Study habits keep the learner perfect in getting knowledge and developing attitude towards things necessary for achievement in different field of human endeavour. Students who develop good study habits at school increase the potential to complete their assignments successfully and to learn the material they are studying. They also reduce the possibility of not knowing what is expected and of having to spend time studying at home. Study habits are the ways that your study habits that you have formed during your school years. Study habits can be good ones, or bad ones. Good study habits include being organized, keeping good notes, reading your textbooks, listening in class, and working every day. Bad study habits include skipping class, not doing your work, etc.

The Impact of Good Study Habit on Academic Achievement of Secondary School Students

Awolesi Oluwadamilola

INTRODUCTION The present day educational sector is becoming increasingly dynamic. The determination of every individual is to attain success and this success affects the personal and social dimensions of life. In this regard, academic performance is one of the major factors that influence individual's success in any educational setting. It is any body's guess that good habits and skills will help us to promote efficiency in our tasks. In education, proper study habits and skills requires proficiency as well as optimum learning quality (Dehghani & Soltanalgharaei, 2014). Productive study requires conceptualization and intention. It could include some skills such as note-taking, observation, asking question, listening, thinking and presenting idea with respect to new discoveries. Thus, students are expected to be interested in learning and must be able to apply requisite skills. On the other hand, inefficient study leads to waste of time and learner's energy (Hashemian & Hashemian, 2014). Study habits and skills like other skills can be taught and learnt. The interplay among motivation, habits, attitudes and behaviors has great impact on the academic performance of students. Study habit is buying out a dedicated scheduled and uninterrupted time to apply one's self to the task of learning. Studying is the procedure of getting information from prints that is information stored in written materials (magazines, newspapers, books). It is an organized gaining of intelligence and an interpretation of information and ideologies that calls for memorizing and usage. Studying can be expressed as the utilization of one's intellectual ability to the gaining, comprehending and arrangement of information; doing it over and over again entails some method of formal learning. Habit is a thing that one does often and almost without thinking; especially something that is hard to stop. A person's habit consists of plethora of ways an individual performs specific and general activity. Habit is relative to person or people. Each human being acts in a unique way. This is so because nature made things

Epoh Sedruol

The nature of study habits of elementary pupils inferred effectiveness and efficiency in school management. Many of the learning activities in school required fully brained pupils with excellent study habit skills. Pupils with good study habit skills dominated and sought to be great leaders of tomorrow. Formation of good study habits especially at the early years had immense implication towards academe. The researcher determined the study habits of the Grade V pupils in Cabalasan Elementary School, Division of Baybay City during the school year 2014-2015 with an end view of recommending ideas for an intervention in improving pupil’s study habits. The study employed normative survey method using checklist of Ralph C. Preston and Morton Botel. Interpretation of data was based on the use of simple percentage, mean and Fischer’s t-test. Results showed that less than half of the time lead in most frequent response in Grade V pupils of Cabalasan Elementary School for the school year 2014-2015 wherein 4 out of 5 descriptive responses showed that there was no significant difference between male and female grade five pupils in study habit contexts such as previewing, reading, note taking while reading, remembering, report writing, listening & taking class notes, preparing for examination, taking examination, planning time and arranging physical setting. The study implied that aside from collaborating with all the stakeholders, continuous learning must be offered in school through provision of time in searching, collecting, organizing and interpreting ideas in a learning hub with available reference books and study equipment for a more relevant and fruitful integration of knowledge. Stressing the importance of macro skills such as listening, reading, writing and speaking in language was of upmost necessity in pupil’s study habits and learning development.

Paul Ryan Cabase

Study habits is how one studies. That is, the habits which students form during their school years. Without good study habits, a student cannot succeed. Thus, this study investigated the impact of study habits on secondary school students' academic performance in the Federal Capital Territory, Abuja. The study was guided by one null hypothesis. The study adopted a descriptive survey research design as its plan. The sample of the study constituted of 1050 senior secondary school students drawn from the Federal Capital Territory, Abuja. The instrument used for data collection was questionnaire. Chi-square was used for data analysis. The finding of the study revealed that there is significant relationship between study habits and students' academic performance. It was recommended that teachers and school guidance counselors should collaboratively guide students on how to develop good study habits; thereby enhancing their academic success.

Ifeoma Obidile

The paper examined study habits as necessary tools for examination success among secondary school students. It listed the major generally accepted patterns of study students can make use of in order to succeed in their studies and examinations with ease. The following recommendations for helping students acquire good study habits are made. These include: policy makers on educational curriculum should ensure that seminar or a course on good study habits should be included in the secondary school curriculum so that students will be helped to inculcate a good study habits to enhancing their examination performances, qualified guidance counsellors should be employed by government and proprietors of secondary schools to be helping students come out of the difficulties they are experiencing in their studies, school authorities should be releasing examination time table on time for proper revision of class work and classrooms and places of study should be devoid of noise, will be well ventilated and lighted, studying environment must be kept clean to avoid unnecessary distractions and infections, Guidance Counsellors and teachers should try to be friendly with the students so that the students will not have any barrier in approaching any of them for clarifications and help and then conclusion.

Scholarly R E S E A R C H Journal

Education is regarded as an agent of nation development so factors that promote academic performance such as effective study habits should be encouraged among students. According to him, the promotion of effective study habits among students should be of profound interest to all stakeholders in the field of education. In India ineffective study habits lead to poor career performance, inefficiency on job, lack of job satisfaction, low productivity, and gross under development and retrogression of the nation’s intellectual advancement. Good study habits make student’s days in school rich, productive and enjoyable. Keyword: Study Habits , effective ,education , academic performance

American Journal of Educational Research

The pattern of behaviour adopted by a student in his/her study is his/her study habits, which reveals his/her personality. Study habits serve as the vehicle of learning and may be seen as both means and ends to learning. This study, thus, investigated the study habits of secondary school science students in the Jalingo metropolis, Taraba State, Nigeria. The study which was guided by three research questions, employed a descriptive correlational research design. The sample of the study is made up of 199 students selected from 5 secondary schools through simple random sampling. Data for the study were generated through a questionnaire, tagged “Science Students’ Study Habit Questionnaire”. Descriptive statistics of frequency counts, mean, and product-moment coefficient of correlation were used for data analysis. The study revealed that the secondary school science students in the Jalingo metropolis have poor study habits and weak academic performance. The study also found a strong posi...

IJARW Research Publication , Rah Rayo

Study habits are at the core of a learner's academic success. It is an action like reading, taking notes, conducting study groups that students perform frequently, and regularly accomplishing the learning goals. It can be defined as effective or counterproductive based on whether it serves the students well. Thus, the study's primary purpose was to determine the relationship between study habits and the students' academic performance. The descriptive-correlation design was utilized to describe the respondents' profile regarding their study habits and academic performance. A total of one hundred twenty-six (126) Grade 11 senior high school learners participated in this study. Moreover, the main research instrument utilized in the study was the Palsane and Sharma Study Habit Inventory. Its eight sub-scales are budgeting time, physical condition, reading ability, note-taking, learning motivation, memory, taking examinations, and health. The findings showed that the respondents' study habits are at a relatively average level. The result revealed no significant relationship between study habits and academic performance. Also, the results showed that the study habits of the students are at a relatively average level. Additionally, enhancing students' study habits are relevant, especially in note-taking, reading ability, and health, thus improving their academic performance.

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Exploring Effective Study Habits: A Comprehensive Survey

In the realm of Education, the 'Study Habits Survey Questionnaire' offers valuable insights into students' learning behaviors and preferences. With questions covering study hours, methods, motivation, and more, this survey aims to uncover the strategies that lead to academic success. By delving into topics like study routines, preferred study environments, and ways to combat distractions, the questionnaire provides a holistic view of students' study habits. Participants can reflect on their study preferences, from solo studying to group sessions, and their preferred tools for organization and relaxation. Stress during exam periods, challenges in specific subjects, and handling procrastination are also crucial aspects explored in this survey. Moreover, the survey delves into learners' preferences in terms of learning styles, environments, and the use of study tools and apps. By gathering responses on study snacks, preferred study times, and the impact of visual, auditory, or kinesthetic learning, this questionnaire sheds light on personalized study approaches. Participants' feedback on study groups, exam preparation, and dealing with procrastination provide valuable data for improving educational strategies. Whether you study in bustling cafes, quiet libraries, or serene parks, this survey highlights the impact of study environments on academic performance. Using a mix of single choice, multiple choice, and open-ended questions, the 'Study Habits Survey Questionnaire' captures a diverse range of perspectives on learning. To gain a comprehensive understanding of study habits and enhance educational outcomes, this survey serves as a valuable tool for students, educators, and researchers. Uncover the secrets to effective studying and optimize your learning experience by participating in the insightful 'Study Habits Survey Questionnaire'.

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Chronically lonely older adults face a higher risk of stroke: harvard study.

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Older adults who experience chronic loneliness face a 56% higher risk of stroke than those who are not lonely, according to a new study from the Harvard T.H. Chan School of Public Health .

Surgeon General Dr. Vivek Murthy called attention last year to a nationwide loneliness and social isolation epidemic , warning that a lack of social connection increases the risk of premature death by more than 60%. Now, Harvard researchers say they are among the first to explore the link between changes in loneliness and stroke risk over time.

The study authors had 12,161 adults 50 and older who had never had a stroke share information about their loneliness. Four years later, the 8,936 people still participating in the study answered the same questions.

They were divided into four groups based on both results — “consistently low” (those who twice scored low on the loneliness scale); “remitting” (those who scored high the first time and low the second time); “recent onset” (those who scored low initially and high at follow-up); and “consistently high” (those who scored high both times).

During the eight-year follow-up period, 601 strokes were recorded among the 8,936 participants. Stroke is the fifth leading cause of death in the US.

The researchers found that the “consistently high” loneliness group had a 56% higher risk of stroke than the “consistently low” group.

Those in the other two groups — “remitting” and “recent onset” — did not have an elevated risk of stroke. Researchers suggest that loneliness’ effect on stroke risk occurs over the longer term.

The findings were published Monday in eClinicalMedicine.

“Repeat assessments of loneliness may help identify those who are chronically lonely and are therefore at a higher risk for stroke,” said lead author Yenee Soh, a research associate in the Department of Social and Behavioral Sciences. “If we fail to address their feelings of loneliness, on a micro and macro scale, there could be profound health consequences.”

Soh pointed out that loneliness and social isolation are not the same. Harvard researchers have clarified that social isolation is a lack of human contact or meaningful relationships, while loneliness is feeling alone because your relationships aren’t fulfilling your need for connection.

Soh’s team hopes additional research sheds light on how the loneliness-stroke association works.

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Eight Recommendations to Promote Effective Study Habits for Biology Students Enrolled in Online Courses

Sharday n. ewell.

a Department of Biological Sciences, Auburn University, Auburn, Alabama, USA

Sehoya Cotner

b Department of Biological Sciences/bioCEED Centre for Excellence in Biology Education, University of Bergen, Bergen, Norway

c Department of Biology Teaching and Learning, University of Minnesota, Minneapolis, Minnesota, USA

Abby Grace Drake

d Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, New York, USA

Sheritta Fagbodun

e Department of Biology, Tuskegee University, Tuskegee, Alabama, USA

Angela Google

f Department of Biology, University of South Alabama, Mobile, Alabama, USA

Lecia Robinson

Paula soneral.

g Department of Biological Sciences, Bethel University, St. Paul, Minnesota, USA

Cissy J. Ballen

To achieve meaningful learning experiences in online classrooms, students must become self-regulated learners through the development of effective study habits. Currently, there is no set of recommendations to promote study habits in online biology learning environments. To fill gaps in our understanding, a working group associated with a research coordination network (Equity and Diversity in Undergraduate STEM, EDU-STEM) convened virtually in June 2021. We identify student barriers to self-regulated learning in online environments and present eight practical recommendations to help biology educators and biology education researchers apply and advance evidence-based study habits in online courses. As higher education institutions continue to offer online learning opportunities, we hope this essay equips instructors with the knowledge and tools to promote student success in online biology coursework.

PERSPECTIVE

The global spread of COVID-19 forced universities to rapidly shift from face-to-face instruction to virtual learning. During this time, students completed their coursework online, and had limited access to their peers, instructors, and other learning supports ( 1 ). Students expressed stress related to learning in this environment, citing challenges with completing coursework as well as a negative perception of online learning ( 1 ). While some students thrived with the increased level of autonomy offered by online learning, others viewed it negatively and struggled with time management, motivation, and focus ( 1 , 2 ). These challenges indicate that students need more guidance and support to achieve meaningful learning experiences in online classrooms. Consistent with this, a survey distributed to faculty in 672 U.S. institutions at the start of the pandemic indicated that the rapid shift to online learning left faculty, many of whom who had no prior experience with teaching online, with limited information on how to best support their students ( 3 ). Specifically, faculty desired more information for students on how to succeed in online learning environments ( 3 ).

Prior to the pandemic, students drove increasing enrollments in online courses across the United States due to their accessibility, flexibility, and convenience ( 4 ). However, students frequently emphasize their preference for face-to-face courses over online courses due to belief that face-to-face courses provide explicit instruction necessary to be academically successful, especially in classes that students perceive as difficult ( 5 ). According to Jaggars (2014), students perceived learning less in online classes and resorted to reading from the textbook to obtain information ( 5 ). Thus, to best support students who enroll in online courses, faculty must understand the perceptions, strategies, and barriers students encounter in these environments.

One of the largest barriers to student success in online courses is self-regulated learning (SRL). SRL refers to how students proactively transform their mental abilities to academic skills through self-generated thoughts, feelings, and behaviors ( 6 ). Students who lack the SRL necessary for online courses experience negative academic outcomes ( 7 , – 10 ). According to Zimmerman’s framework of SRL, there are three critical components by which self-regulated learners engage in their own learning: metacognition, motivation, and behavior ( 6 , 11 ). For example, self-regulated learners may have the ability to monitor their own learning (metacognition), have intrinsic interest in their studies (motivation), and employ effective study habits (behavior) ( 5 , 6 , 11 ). In this essay, we focus on the application of appropriate study habits because students report significant struggle in this area, particularly in online environments that demand high-SRL skills ( 12 , 13 ). Study habits encompass a variety of behaviors that include what strategies students use to learn, understand, and retain course content, how much time is spent studying, and how students distribute their study time over the course of a semester ( 12 , 14 ). As the transition to emergency remote learning demonstrated, these skills are underdeveloped in students, particularly those enrolled in large, introductory classes, and many students developed a negative attitude toward online learning as a result ( 1 , 2 ). How can faculty equip their students with the cognitive tools necessary to study effectively and succeed in the online environment?

To address this question, faculty must first understand why students relied on ineffective study habits during online learning. In this paper, we present a framework for challenges and solutions related to the promotion of study habits in the online environment. We explored these ideas during a breakout discussion of participants from a Research Coordination Network, Equity and Diversity in Undergraduate STEM (EDU-STEM) in June of 2021. During this breakout session, a group of faculty who represent a variety of institutional types, including community colleges, private undergraduate colleges, research-intensive institutions, and minority serving institutions gathered to discuss experiences with emergency remote teaching and identify best practices for supporting students in the online learning environment. The goal of this session was to come to a consensus regarding student challenges and best practices to promote successful study habits in online instruction. During the pandemic, we taught large enrollment introductory biology classes through asynchronous or synchronous Zoom sessions and used a variety of learning management systems (LMS) (e.g., Canvas, Moodle, Blackboard) to distribute course-related information to students.

Here, we identify challenges for student development of effective study habits in online courses and offer eight recommendations for instructors to help students overcome these challenges and develop the tools necessary to be successful in biology.

CHALLENGES FOR STUDENT DEVELOPMENT OF EFFECTIVE STUDY HABITS IN ONLINE COURSES

A goal of college courses is to teach students how to be self-regulated learners, or students who actively participate in their own learning by adjusting their efforts, approaches, and behaviors to achieve their learning goals ( 6 , 11 , 12 ). Students often enter college with underdeveloped self-regulatory skills ( 11 , 12 , 15 ). Specifically, students lack the ability to effectively assess their learning and often feel that they learn more from cognitively superficial study habits such as re-reading the textbook or their lecture notes ( 11 ). This outcome is particularly common among students enrolled in online coursework. Due to limited instructor–student interaction, online courses require students to assume greater responsibility for their learning, to actively monitor their performance, and to apply appropriate study strategies to be academically successful ( 9 , 16 ). However, despite the importance of this skill, students enrolled in online classes may be unaware of how to effectively implement SRL or face serious challenges out of their control that result in poor performance outcomes in online courses ( 4 , 17 ).

Below we summarize discussions among the contributing authors, who are biology instructors from a Research Coordination Network (Equity and Diversity in Undergraduate STEM, or EDU-STEM) about central challenges students face in their efforts to study and prepare for biology courses. These include: (i) low motivation and low self-efficacy; (ii) depression and anxiety; (iii) Zoom fatigue; (iv) inability to access network of peers; and (v) work/life balance ( Table 1 ).

TABLE 1

Challenges students experience when attempting to prepare and study for online biology classes

Low motivation and low self-efficacy

Students reported that the abrupt shift from face-to-face learning to online learning environments resulted in difficulties with SRL ( 1 ). Self-efficacy (student perception that they are capable of learning) and motivation (intrinsic motivation to learn) have been identified as factors that contribute to SRL development in online environments ( 1 , 16 , 17 ). Students who have high self-efficacy and are highly motivated tend to appropriately control their learning process and utilize appropriate study strategies in order to achieve their learning goals. However, students who have low self-efficacy or lack motivation fail to use these strategies and experience negative academic outcomes as a result (e.g.,- spending more time on assignments, failing to submit assignments on time, and submitting poor quality work) ( 1 , 18 ). Research into online learning environments corroborates previous research; specifically, Landrum (2020) found student confidence in their ability and motivation to learn in an asynchronous, online environment in the absence of peers and instructors to be a predictor of student performance and persistence ( 19 ).

Anxiety and depression

Prior to the COVID-19 pandemic, institutions across the United States were reckoning with a growing mental health crisis, with an increasing number of students seeking mental health treatment for anxiety and depression ( 20 , 21 ). Anxiety is a common mood disorder that is characterized by excessive worrying and hypervigilance. It is often associated with depression, which is characterized by persistent feelings of sadness and hopelessness ( 21 , – 23 ). These feelings can be accompanied by loss of energy, difficulty concentrating, and difficulty sleeping ( 21 ). Given that mental health can affect student motivation and concentration, it has been identified as a leading barrier to academic success ( 21 , 24 ). During COVID-19 online learning, the pandemic lockdown exacerbated mental health issues such as depression in undergraduate students due, in part, to concerns about their own well-being, as well as the health of their friends and family, less interaction with others, and less community support ( 24 , – 29 ). Women, students of color, LGBTQ+ students, and students from lower-than-average socio-economic backgrounds were disproportionately affected by lockdown and reported higher levels of anxiety and depression ( 20 , 25 , 30 , 31 ). Many students reported that the transition to online classes and difficulty with online learning were major stressors that resulted in higher rates of anxiety and depression ( 1 , 20 , 24 ). Consequently, students reported increased workloads, more difficulty in completing academic tasks due to physical isolation from instructors or teaching assistants, and struggling to concentrate ( 1 , 24 ). Consistent with these findings, undergraduate and postgraduate students reported that mental health difficulties negatively affected their ability to study ( 32 ). Despite the urgent need for increased mental health support, previous research showed students perceived barriers to seeking help from professionals or peers due to fear of judgment ( 21 , 24 ). Interestingly, despite the difficulties reported with online coursework, some students reported the use of effective study habits (e.g., setting a study schedule) as a coping mechanism for their anxiety ( 24 ).

Zoom fatigue

The COVID-19 pandemic caused a rapid rise in the use of video conferencing systems, such as Zoom, Google Meet, Blackboard Ultra, and Microsoft Teams. For example, Zoom video conferencing increased from approximately 10 million daily Zoom meeting participants in December 2019 to 200 million in March 2020 and 300 million in April 2020 ( 33 ). The increase in screen and sitting time caused many users to experience fatigue or burnout. A new phrase, Zoom fatigue, or Zoom burnout, paralleled the growth in Zoom usage peaking in popularity in late April 2020 and July 2021 respectively (data source: Google Trends [ https://www.google.com/trends ]).

Zoom fatigue refers to the mental and physical exhaustion people feel after participating in prolonged periods of virtual meetings. It is caused by excessive amounts of closeup eye gaze, cognitive load, increased self-evaluation from staring at video of oneself, and constraints on physical mobility and communication ( 34 ). Users reported increases in physical, behavioral, and psycho-emotional problems ( 35 , 36 ), including difficulty concentrating, physical exhaustion, anxiety, irritability, headache, eye strain, and increased pessimism. Furthermore, Zoom fatigue has been attributed to the fatigue associated with concerns regarding self-presentation (i.e., being watched on camera enhances need to manage impression and turns focus inward) ( 37 ). Ultimately, this limits participant engagement with the virtual meeting ( 37 ).

Unsurprisingly, Zoom fatigue has resulted in students reporting moderate to considerable difficulty with online learning. Learning, even in online environments, requires active engagement, and students have not received training on how to actively engage in asynchronous or synchronous Zoom sessions ( 38 ). As a result, students reported increased distractions and struggled with remembering the materials presented during asynchronous or synchronous sessions due to the passive intake of information and lack of engagement in the content that would promote deeper learning ( 38 ). As a result, students may rely heavily on passive strategies (e.g., re-reading the textbook, re-watching lecture videos) during their study periods to fill the gaps in their knowledge.

Isolation from peers/ability to access network of peers

Past research highlights how undergraduate students rely on their peers to teach and learn disciplinary content related to coursework ( 39 , 40 ) and employ effective study habits ( 41 , 42 ). Research on information seeking behavior , or the way people search for and utilize information ( 43 ), has demonstrated that students and the public actually prefer to obtain information from human sources ( 44 ). For example, students’ information seeking behavior may involve actively finding relevant information about the syllabus from a peer to prepare for an exam.

During face-to-face instruction, students are immersed in classrooms with other students and plenty of opportunities exist to interact with peers before, during, and after class in such a way that supports collaborative learning. In online learning environments, however, instructors or course developers must implement virtual structures that support collaborative learning with peers. The lack of default opportunities to engage in discussions with peers represents a potential obstacle for students, who will not reap the benefits of these interactions in their learning. These obstacles may be particularly high for first-year students, transfer students, or those who are unfamiliar with others who are in the class. Previous research documented how students’ studying for exams in large active learning organismal biology classes differed 1 week and 1 month after a university's decision to transition to emergency remote instruction due to COVID-19 ( 45 ). They found that at both time points, one of the largest concerns reported by students related to a lack of access to their in-class assigned groups. One student acknowledged, “I was unable to study with friends and had no way of knowing if my knowledge had holes in it.” This reflection speaks to the importance of student access to their network of peers in preparing for in-class assessments.

Work-life balance

Students in online learning environments may experience challenges in managing the expectations of work, school, and home ( 46 ). In traditional face-to-face learning environments, there are firm barriers between learning time, family time, work time, and leisure time that allow students to schedule and complete activities associated with each task (e.g., setting up dedicated study time) ( 46 ). However, as online learning became increasingly prevalent during the COVID-19 pandemic, these boundaries between school, family, work, and leisure time began to blur and students struggled with adjusting their behaviors to balance each of these domains ( 1 , 46 ). The pandemic highlighted the sizeable population of students for whom college was not their only focus. Such students may hold one or two jobs to cover tuition costs and other living expenses. Others may have family responsibilities such as caring for a younger sibling, elderly parent(s), or caring for their own family and children.

EIGHT RECOMMENDATIONS TO DEVELOP STUDENT STUDY HABITS IN ONLINE BIOLOGY COURSES

After discussing challenges for students and why some might rely on ineffective study habits during online learning, we explored recommendations for instructors during a breakout discussion of participants from Research Coordination Network EDU-STEM. While each recommendation will profit from more research in the context of undergraduate biology, they represent the opinions of experienced faculty who teach biology from a range of institutions and serve as a starting point into empirical work on these topics. The eight recommendations aimed at promoting effective study habits include (i) establish content (and digital) learning objectives; (ii) align assessments and assignments with learning objectives; (iii) high quality feedback; (iv) increase scaffolding; (v) incorporate multiple due dates; (vi) incorporate online formative assessments; (vii) provide resources outside of textbook and recorded lectures; and (viii) facilitate student-content engagement with interactive instructional materials ( Table 2 ).

TABLE 2

Recommendations for developing effective study habits

Recommendation 1: establishing content (and digital) learning objectives

We recommend that online instructors select and articulate not only biology content and science process learning objectives, but also digital learning objectives that develop the skills and confidence of students in the effective use of the digital technology that supports their learning. In the beginning weeks of a course, instructors can easily create digital objectives for navigating the LMS (e.g., “students will be able to access course announcements”). However, students need continuous practice using these online tools and it is important for instructors to incorporate their content objectives with digital objectives. For example, instructors who wish for their students to gain core knowledge may articulate low-level Bloom's objectives and select a quizzing strategy through adaptive learning programs that allow students to practice factual knowledge. In this instance, it is equally important for instructors to name the learning objective for the digital output (e.g., “students will demonstrate proficiency in timed online multiple-choice quizzing”) and provide adequate training for how to use this platform of practice effectively (e.g., “treat the answer choices as multiple true-false statements for extra practice”). Similarly, instructors may wish for their students to apply recently learned content to a real-world scenario and may require students to complete the assignment in online collaborative groups. Thus, for this assignment the digital objective would be “students will demonstrate proficiency in accessing student groups on the LMS and contacting groupmates.” In doing so, student content learning and digital skills are made as explicit as the modality in which they will demonstrate those outcomes. Class time may be used to model effective online learning study skills calibrated to the learning objectives and digital mode, and students may be assigned and encouraged to use and transfer these skills independently as they grow in their metacognitive awareness and self-regulation.

Although low-level Bloom’s objectives are commonly utilized in online spaces ( 47 ), higher order skills may be assessed using alternative assessment styles in the digital space. For example, conceptual models may be assessed in a drawing app (Google JamBoard) or problem-solving, and argumentation skills may be assessed using video apps. Regardless of the digital output, the core tenet of explicitly stating the digital learning objectives and outputs along with the desired content and scientific skill objectives is key.

Recommendation 2: aligning assessments and assignments with learning objectives

Alignment of course activities and assessment methods with learning objectives is critical for effective course design across in-person and online learning environments ( 48 , – 53 ). Through this alignment, instructors can clearly communicate to students what is expected of them, and work shows that students find properly aligned objectives helpful in highlighting what they are expected to know ( 54 ). Additionally, undergraduate science students believe that learning objectives are a helpful tool to narrow down and organize their studying while preparing for exams ( 54 ). But how do students use learning objectives to study? In a study conducted by Osueke et al. (2018), students indicated that they use learning objectives for self-assessment (e.g., answering the learning objectives as questions or self-testing using the learning objectives) and as a resource for studying (e.g., using the learning objectives as a study guide) ( 54 ).

Given that online students may not know how to use learning objectives as a resource for their learning, we recommend that instructors not only clearly define and explicitly communicate learning objectives to students, but also provide explicit instruction on how to use learning objectives for self- assessment.

Recommendation 3: high quality feedback

In large foundational face-to-face STEM courses, students commonly receive formal instructor feedback only a few times throughout the semester, generally after large consequential exams that account for a significant part of the students’ grades. However, it’s easier for instructors to engage in informal dialogue and gauge student understanding in face-to-face settings, and students may benefit from unstructured or unplanned feedback on assignments, assessments, or other important information. In some online learning environments, such as those where the instructor is teaching an online class of black screens, it is more difficult to ‘read the room’ and know when students need clarification on a topic. In these online contexts, providing high quality feedback becomes a crucial element of the learning process ( 55 ). Student reports also show instructor feedback is used as a method for improving learning or study strategies ( 56 ). Students struggle with constructing meaning from online content and identifying concepts to study, underlining the need for instructors to provide high quality feedback on student assignments and assessments. This fosters student motivation and can provide information to help shape learning ( 55 ).

Recommendation 4: scaffolding

The incorporation of specific design elements, such as active learning strategies, student engagement, and assessment strategies, guide students in how to manage their time, self-assess their understanding of material, and promote satisfaction in learning. These design elements, also known as scaffolding, refer to the teacher-generated support a learner is given to accomplish a specific task ( 57 ). For example, an instructor can teach students how to engage with recorded lectures by providing guided note taking sheets ( 58 ). Additionally, instructors can encourage students to self-assess by providing frequent short practice tests and quizzes ( 58 ). As a learner achieves mastery in a specific task, the teacher may remove the support and pass the responsibility of learning on to the learner ( 57 ). Interestingly, scaffolds also allow students to think deeply about the content and are particularly effective in helping students develop study strategies and time management skills ( 17 ).

Prior to and during the pandemic, students commonly reported that online learning was subpar compared to face-to-face learning and that they simply did not learn as much in their online classes ( 1 , 58 ). Students also cited poor time management, inability to assess learning, and lack of access to supporting resources as barriers that contributed to their negative experience and poor academic outcomes ( 1 , 45 ). However, by including scaffolds in their learning management systems, instructors can elicit appropriate study habits from students.

Recommendation 5: multiple due dates

Students prefer clear and consistent due dates for assignments in online courses, and previous work shows this relates to their self-perceived learning and learning satisfaction ( 58 ). However, during the COVID-19 pandemic, students frequently expressed issues with procrastination and turning work in on time despite having a clear due date ( 1 ). This, along with a perceived increase in workload and inability to construct meaning from recorded lectures, can result in students using ineffective study habits (e.g., “cramming”) during their study time. To limit these issues, we recommend that instructors move due dates to multiple times during the week instead of requiring students to submit all of their assignments on one day ( 17 , 59 ). Setting multiple due dates allows students to work in smaller, manageable time increments. Additionally, this easy change models the highly effective study strategy of spacing (i.e., studying across multiple sessions instead of cramming) for students. Specifically, setting multiple due dates encourages students to work on assignments at multiple points during the week and ultimately promotes greater long-term learning ( 12 , 17 ).

Recommendation 6: incorporating online formative assessments

Due to Zoom fatigue and other factors affecting focus, students have struggled with constructing meaning from the lectures posted by instructors. Interestingly, prior studies have demonstrated that online formative assessments are essential for gaining, refocusing, and extending student attention following STEM lectures ( 58 ). Therefore, to assist students in understanding the content presented, it is recommended that instructors incorporate frequent, low-stakes online formative assessments (i.e., activities that are a small portion of students’ grades and are intended to generate feedback on learning progress) ( 60 ). Formative assessments encompass a variety of activities such as weekly quizzes, homework assignments, group discussions, and in-class polling. While frequent, low-stakes formative assessments are important for students in all classroom contexts, they are especially important for online learners who may struggle with self-regulated learning because they provide students with immediate feedback and explanations that students can use to modify their learning ( 58 ). Thus, instructors should incorporate online formative assessments into their LMS. These assessments can be created through various learning management systems such as Canvas, Blackboard, or Moodle. Alternatively, instructors can use tools such as EdPuzzle ( www.edpuzzle.com ), Quizizz ( www.quizizz.com ), Kahoot! ( https://kahoot.com/ ), or Quizlet ( www.quizlet.com ) to create formative assessments for their students.

Recommendation 7: providing resources outside of textbook and recorded lectures

In an institutional survey given to students enrolled in online STEM courses, students indicated that they enjoyed course-related videos that allowed for greater understanding of course content ( 58 ). While some students are considered to be digital natives, or those who were exposed to computers and digital technology from an early age, many students struggle with using digital tools, such as navigating learning management systems, for academic purposes. This means that the tools provided to students intended to enhance their learning may inadvertently serve as a barrier to learning. We suggest that instructors provide links to other resources (e.g.,- YouTube videos, instructor generated guided notes, simulations) that provide students with different ways to engage with and conceptualize the content ( 17 ).

Recommendation 8: facilitate student-content engagement with interactive instructional materials

Learner interaction with content has previously been identified as a key factor that supports learning in online courses ( 61 ). This interaction can take a number of forms (e.g., watching instructional videos, interaction with multimedia, and searching for information) and requires instructors to take an active role in facilitating sustained engagement with the course material ( 61 , 62 ). Thus, online instructors are encouraged to invest time in searching for interactive instructional materials ( 62 ). However, during the COVID-19 pandemic, instructors were forced to rapidly shift to online teaching, and many had to do so without previous online teaching experience. As a result, like many newcomers to online teaching, instructors simply replicated their traditional classroom model to an online platform without alteration to account for the new instructional context ( 63 ). This left some students struggling to effectively engage with and study the content, which may contribute to the perception that all online learning was less interactive ( 64 ) and less motivating ( 65 ) than face-to-face instruction. Instructors can address some of these concerns by creating interactive, online content compatible with asynchronous or synchronous environments. Interactivity can enhance student motivation by increasing autonomy, such that the user must make choices and direct the pace of their own learning, and a sense of competence, such that lessons can be scaffolded so that novel concepts are not introduced until initial concepts are mastered ( 66 , – 68 ).

Several tools exist for creating interactive content—tools that go beyond what is native to an existing LMS. Tools that are either free or relatively low-cost include Edpuzzle ( https://edpuzzle.com/ ), Quizizz ( www.quizizz.com ), Kahoot! ( https://kahoot.com/ ), Quizlet ( www.quizlet.com ), Nearpod ( www.nearpod.com ), Wordwall ( https://wordwall.net/ ), and H5P ( https://h5p.org/ ). These tools allow the instructor to create activities (e.g., multiple choice quizzing, interactive video presentations, simulations) that are scaffolded, tailored to course content, and aligned with course outcomes ( Fig. 1 ). Further, these tools can be embedded into several existing LMS platforms such Canvas, Moodle, and Blackboard, and shared easily with colleagues.

Examples of interactive activities on H5P from Cotner and Wassenberg ( 72 ).

The goal of this essay was to identify challenges students face studying for online biology courses and to provide recommendations for instructors to foster the development of effective study strategies. Our recommendations were informed by our experiences with teaching online biology courses and by the current state of knowledge regarding best practices for online teaching. As instructors communicate expectations to students through pedagogical choices (e.g., use of instructional time, assignments, course structure, scaffolding, and organization), students will adjust to these situational and environmental cues with explicit training and modeling for how to study and master the material in the online learning space. We hope that iterative, high-structure, and developmental approaches in the online learning space will result in similar positive impacts as previously reported in physical classrooms ( 69 , – 71 ).

ACKNOWLEDGMENTS

We thank the following members of the Ballen lab for valuable feedback on the manuscript and early discussions on this topic: Abby Beatty, Ariel Steele, Chloe Josefson, Emily Driessen, Todd Lamb, Peyton Brewer, William Grogan, Quinn Johnston, and Rachel Youngblood. Additionally, we thank Jordan Harshman, Ngawang Gonsar, and Marcos E. Garcia-Ojeda for their contributions to early discussions on this topic. This work was supported by a research coordination network grant NSF DBI-1919462. Any opinions, findings, conclusions, and recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

The authors certify that they have no affiliations or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent licensing arrangements) or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge, or beliefs) in the subject matter or materials discussed in this manuscript.

We declare no conflicts of interest.

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Immigration, gender identity, racial diversity and views of a changing society

Table of contents.

• Voters’ views about race and society, the impact of the legacy of slavery
• Most voters, but not all, view the nation’s diversity as a strength
• How should the country handle undocumented immigrants currently in the U.S.?
• Attitudes toward hearing other languages in public places
• Biden and Trump supporters’ views about discussing America’s historical successes, failures
• How does the U.S. compare with other countries?
• Views of women’s progress
• How much of a priority should marriage and children be?
• Abortion, IVF access and birth control
• Views of gender identity
• Voters’ attitudes toward use of gender-neutral pronouns
• Societal impact of more social acceptance of lesbian, gay, bisexual people
• Religion and government policy
• How much influence should the Bible have on the nation’s laws, if any?
• Views on the federal government’s role in promoting Christian values
• Most voters say it is not necessary to believe in God to be moral
• Is the justice system too tough on criminals, or not tough enough?
• Policing and law enforcement
• How Trump, Biden supporters view gun rights and ownership
• Views on the increasing number of guns in the U.S.
• Acknowledgments
• The American Trends Panel survey methodology

Pew Research Center conducted this study to understand voters’ political values related to cultural issues in the context of the 2024 election. For this analysis, we surveyed 8,709 adults, including 7,166 registered voters, from April 8 to 14, 2024. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology . 

Here are the questions used for the report and its methodology . 

The 2024 presidential campaign is taking place amid intense debates over such topics as immigration, growing racial and ethnic diversity in the United States, the changing American family, crime and reproductive issues.

These topics sometimes are grouped together as “culture war” or “woke” issues.

On most – but not all – of these topics, voters who support President Joe Biden and former President Donald Trump have starkly different opinions. Yet in many cases, Biden and Trump supporters are themselves sharply divided.

Across more than 30 measures, some of the widest differences are on issues that have divided Americans for decades: the role of guns in society, as well as race and the legacy of slavery.

Yet, Biden and Trump supporters also have very different opinions across many other topics likely to be focal points in the campaign: gender identity and sexual orientation, crime and policing, reproductive issues, the influence of religion on society and the changes that have transformed life in the U.S. in recent decades.

A new survey by Pew Research Center of 8,709 adults – including 7,166 registered voters – conducted April 8-14, 2024, examines the political values of the Biden and Trump coalitions that underlie policy attitudes in many of these areas.

Jump to read about Biden and Trump supporters’ views on: Race and racial diversity | Immigration and language | American history | Gender and family | Gender identity and sexual orientation | Religion | Crime and policing | Guns

Among the major findings:

Enduring divisions on race and the legacy of slavery. Just 27% of registered voters who support Trump say the legacy of slavery affects the position of Black people in America today a great deal or fair amount; 73% say it has little or no impact.

Opinions among Biden supporters are nearly the opposite: 79% say slavery’s legacy still affects the position of Black people, while 20% say it has not too much or no effect.

Wide gaps on gender identity and same-sex marriage. While Americans have complex opinions on gender identity and transgender rights , a growing share of voters (65%) say that whether a person is a man or woman is determined by the sex they were assigned at birth. About a third (34%) say someone can be a man or woman, even if that differs from their sex at birth.

• Nearly all Trump supporters (90%) say gender is determined by sex at birth. By contrast, Biden supporters are more divided. About six-in-ten (59%) say gender can be different from sex at birth; 39% say gender is determined by sex at birth.
• Nearly a decade after the Supreme Court legalized same-sex marriage , Biden and Trump supporters have starkly different views of the impact of that historic ruling. Biden supporters are about five times as likely (57%) as Trump supporters (11%) to say legalization of same-sex marriage is good for society.

Most Trump voters now favor a “national effort to deport” all those in the U.S. illegally. Opposition to allowing undocumented immigrants to stay in the country legally if they meet certain requirements has risen in recent years, driven largely by Republican and Republican-leaning registered voters.

• Nearly two-thirds of Trump backers (63%) support a national effort to deport all those in the country illegally, compared with just 11% of Biden supporters.

Divided views of the criminal justice system. A majority of voters (61%) say the criminal justice system is generally “not tough enough on criminals.” Just 13% say the system is too tough, while 25% say it treats criminals about right.

• Trump supporters (81%) are about twice as likely as Biden supporters (40%) to say the criminal justice system is not tough enough on criminals.
• Yet, there are much narrower differences in several priorities for the police and law enforcement: Overwhelming majorities of Biden and Trump supporters say it is extremely or very important for police and law enforcement to keep communities safe and to treat people of all racial and ethnic groups equally.

The changing American family. The structure of American family is very different than it was 40 or 50 years ago . Biden and Trump supporters view these changes very differently:   

• Roughly three times as many Trump supporters as Biden supporters say society is better if people prioritize marriage and family (59% vs. 19%).
• And Trump supporters are far more likely to take a negative view of the nation’s falling birth rate: 47% say people having fewer children is a bad thing, compared with 23% of Biden supporters.

Divisions on abortion, more agreement on availability of contraceptives. Since the Supreme Court’s 2022 decision overturning Roe v. Wade, which guaranteed a right to abortion, support for legal abortion has ticked up in both parties.

• Today, 88% of Biden supporters say abortion should be legal in all or most cases; 38% of Trump supporters say the same.

By contrast, voters – including large majorities of both candidates’ supporters – overwhelmingly say the wide availability of birth control pills, condoms and other forms of contraception is good for society.

Broad support among voters for discussing America’s historical successes – and its flaws. The survey finds that while Biden and Trump supporters have profoundly different attitudes on many cultural issues, they mostly support the discussion of America’s historical successes, as well as its flaws.

• Nearly identical shares of Biden (74%) and Trump supporters (71%) say it is extremely or very important to have public discussions about the country’s historical successes and strengths.
• 78% of Biden supporters and 60% of Trump supporters say it is at least very important to have public discussions about the country’s failures and flaws.

Voters are very positive about more open discussions of mental health. More than eight-in-ten voters (87%) say that more people openly discussing mental health and well-being is good for society. This includes large majorities of both Biden (94% good thing) and Trump supporters (79%).

Related: Who do Americans feel comfortable talking to about their mental health?

There is broad skepticism about the increased use of artificial intelligence (AI) in daily life. More than half of voters (55%) say this is bad for society, while 21% see this as a good thing (24% say it is neither good nor bad). There are only modest differences in these views between Trump supporters (59% say this is bad for society) and Biden supporters (51%).

Related: Growing public concern about the role of artificial intelligence in everyday life

Voters’ comfort level with some common – and less common – experiences

To some extent, voters’ political values are reflected in whether or not they’re comfortable with fairly common experiences.

A large share of voters (80%), including sizable majorities of Biden and Trump supporters, say they are comfortable with someone they don’t know saying they will keep them in their prayers.

Most women in opposite-sex marriages continue to take their husbands’ last names when they marry. Still, three-quarters of voters say they are comfortable with women not taking their husbands names.

Trump supporters are less comfortable than Biden supporters with women not taking their husbands’ last names. And among men who support the former president, 44% are uncomfortable with this practice, compared with 29% of women who support Trump.

There is a wider gap between Biden and Trump voters in comfort with people speaking a language other than English in public places in their communities. More than eight-in-ten Biden supporters (83%) are comfortable hearing languages other than English, compared with a narrow majority of Trump supporters (54%).

And, reflecting the wide divide between the two sides in opinions on transgender issues, just 20% of Trump supporters say they are comfortable with someone using “they/them” instead of “he” or “she” to describe themselves. More than three times as many Biden supporters (66%) – including 79% of Biden supporters under age 50 – say they are comfortable with the use of these gender-neutral pronouns.

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Americans’ Views of Government’s Role: Persistent Divisions and Areas of Agreement

6 facts about presidential and vice presidential debates, biden, trump are least-liked pair of major party presidential candidates in at least 3 decades, more than half of americans are following election news closely, and many are already worn out, americans have mixed views about how the news media cover biden’s, trump’s ages, most popular, report materials.

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Association of maternal dietary habits and infant mthfr gene polymorphisms with ventricular septal defect in offspring: a case–control study.

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Ruan, X.; Li, Z.; Zhong, T.; Lei, R.; Luo, M.; Sun, M.; Qin, J. Association of Maternal Dietary Habits and Infant MTHFR Gene Polymorphisms with Ventricular Septal Defect in Offspring: A Case–Control Study. Nutrients 2024 , 16 , 2005. https://doi.org/10.3390/nu16132005

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Ruan, Xiaorui, Ziye Li, Taowei Zhong, Ridan Lei, Manjun Luo, Mengting Sun, and Jiabi Qin. 2024. "Association of Maternal Dietary Habits and Infant MTHFR Gene Polymorphisms with Ventricular Septal Defect in Offspring: A Case–Control Study" Nutrients 16, no. 13: 2005. https://doi.org/10.3390/nu16132005

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