Investigating Students’ Self-Regulated Learning While Learning Electric Circuit Concepts with Enhanced Guided Notes

First-year higher education (HE) students experience different challenges during their studies. These challenging learning situations can trigger self-regulated learning (SRL) skills, which students use to handle these situations. Thus, the aim of this study is to investigate (a) first-year HE students’ cognitive, motivational and emotional challenges experienced in both individual and collaborative learning situations and (b) the relationship between SRL skills and experienced learning challenges. Participants included 107 first-year pre-service teachers. Data consisted of students’ self-reports via (a) open-ended answers on a challenge questionnaire and (b) Likert-scale items from MSLQ and MRS questionnaires. Based on students’ SRL profiles, differential effects on the challenging experiences were investigated. The results show that different aspects related to students’ cognition, motivation, emotions and well-being were challenging for students. Also, connections were found between students’ SRL skills and the types of experienced learning challenges. Students with high SRL reported fewer learning challenges related to motivational aspects and more challenges related to cognitive aspects than students with low SRL.

This study aimed to investigate the impact of self-regulated learning (SRL) skills on the academic success of non-commissioned officer (NCO) students within a Special Vocational College (SVC) belonging to the government context. As blended courses become increasingly prevalent, there is a growing interest in understanding the role of SRL, a critical determinant of academic performance. While SRL has garnered substantial attention in higher education, limited research has focused on its relevance within SVCs. Furthermore, little is known about the factors influencing students' SRL levels in online learning settings and their subsequent impact on course performance. Therefore, this study endeavors to identify the factors that influence SVC students' SRL and assess how it impacts success in blended courses. The study was conducted during the Fall semester of 2022-2023, encompassing five distinct compulsory blended courses and involving a total of 203 SVC students. We utilized a path model, expanding upon the framework proposed by Liaw and Huang in 2013, to assess the influence of SRL on academic achievement. The findings demonstrated that students' perceptions of the interactivity in the learning environment (ILE) and their perceived self-efficacy (PSE) had a positive and significant impact on their perceived satisfaction (PS). Additionally, ILE, PSE, and PS significantly influenced the perceived usefulness (PU) of the learning management system (LMS). Furthermore, ILE, PU, and PS emerged as significant predictors of students' SRL skills. However, the observed results did not entirely align with the expected impact on academic success. The study's findings shed light on the complex relationship between course achievement and SRL in blended learning settings, as well as the interrelated factors at play. The practical implications of these findings extend to how LMS administrators can support students in blended courses in becoming more self-regulated learners.

The focus of education is increasingly on learners’ ability to regulate their own learning within technology-enhanced learning environments. Prior research has shown that self-regulated learning (SRL) leads to better learning performance. However, many learners struggle to productively self-regulate their learning, as they typically need to navigate the myriad of cognitive, metacognitive, and motivational processes that SRL demands. To address these challenges, the FLoRA engine is developed to help students, workers, and professionals improve their SRL skills and become productive lifelong learners. FLoRA incorporates several learning tools that are grounded in SRL theory and enhanced with learning analytics (LA), aimed at improving learners’ mastery of different SRL skills. The engine tracks learners’ SRL behaviours during a learning task and provides automated scaffolding to help learners effectively regulate their learning. The main contributions of FLoRA include (1) creating instrumentation tools that unobtrusively collect intensively sampled, fine-grained, and temporally ordered trace data about learners’ learning actions; (2) building a trace parser that uses LA and related analytical techniques (e.g., process mining) to model and understand learners’ SRL processes; and (3) providing a scaffolding module that presents analytics-based adaptive, personalized scaffolds based on students’ learning progress. The architecture and implementation of the FLoRA engine are also discussed in this paper.

In order to manage the demands of university studies, research suggests that university students should possess efficient self-regulated learning (SRL) skills. The use of mobile learning is believed to enhance SRL skills. Yet, despite the potential benefits of mobile learning, many first-year students encounter challenges in using mobile devices to foster self-regulated learning skills. It is against this backdrop that this study aimed to examine how first-year medical students utilisee mobile learning to foster self-regulated learning. This study employed a Explanatory Sequential Study Design , combining both quantitative and qualitative data. It used the interpretativist and pragmatic paradigms to understand how students perceive and use mobile devices for self-regulated learning. The interpretivist paradigm focused on understanding students’ perspectives, while the pragmatic paradigm aimed to identify effective ways of using mobile devices to promote self-regulated learning. Participants to this study were first-year medical students. The mixed-methods approach aimed to provide a comprehensive understanding of the research problem by collecting data through various methods. Questionnaires gathered quantitative data, while participatory observation, reflective workshops, and focus group discussions provided qualitative data. The theoretical frameworks that guide the study include the Unified Theory of Acceptance and Use of Technology model (UTAUT) (Venkatesh et al., 2003) and Vygotsky's (1978) socio-cultural theory (SCT). The study findings revealed that mobile devices were used by first year medical students to manage and control their learning, both inside and outside the classroom. Notably, significant improvements were observed in cognitive learning strategies, metacognitive self-regulation strategies and resource management learning strategies, including time management. Additionally, the study found that first-year medical students had a positive perception of mobile learning. Furthermore, mobile devices were generally perceived as enablers of self-regulated learning (SRL), providing flexibility, convenience, and access to diverse learning resources. However, distractions and interruptions posed challenges to focus and attention. To mitigate these challenges, strategies such as device management and setting boundaries were suggested. Moreover, first-year medical students expressed the need for support in developing SRL through mobile learning. Guidance in selecting effective mobile applications, opportunities for collaborative learning, and technological skill training were identified as essential forms of support. The study thus recommends integrating mobile learning into curricula to enhance self-regulated learning skills in higher education students, especially among first-year students. Higher education institutions should establish deliberate policies and initiatives for mobile learning programs, especially for first-year students. Educators should offer guidance and training on using mobile learning tools effectively, including information searching skill. However, students should be cautious about distractions from the use of mobile devices.

Developing problem solving competence is one of the main goals of Mathematics Education. Self-regulated learning skills are important for success in problem solving. The aim of this paper is to present the results of a research about 10-11 years old pupils’ self-regulated learning and problem solving skills and the relation between these two skills. The results show that more than three quarters of 10-11 years old pupils like Mathematics, but only the half of them likes to solve non-routine problems. The positive attitude towards Mathematics is influenced by pupils’ positive experiences on solving problems and their beliefs in the utility of Mathematics in their future. Most of the pupils don’t give up if they can’t solve the problem, they go over the text again, they try to find similar worked examples, they ask for help. There is a mild correlation between pupils’ self-control and problem solving skills, a weak correlation between pupils’ attitude towards Mathematics and their problem solving skills.

For K-12 teachers to develop effective teaching skills, integration of role modeling strategies into teaching and learning process as a dimension of selfregulated learning is of the foremost value. Role modeling strategy training through a hybrid professional development model bears the potential to serve as a facilitating component in promoting K-12 teachers’ instructional competence. Conducted within the self-regulated learning framework, this study suggested findings of a teacher professional development training aimed at role modeling strategy implementation at K-12 level. Pursuing a mixed-method model, the current research was performed with 16 teachers who were trained and supervised to integrate role-modeling strategies into their teaching context. In this study, the data sources were role-modeling- integrated lesson plans, trainers’ feedback on these lesson plans, and online student products. The data collection methods included lesson plan evaluation through a role-modeling rubric in a quantitative fashion, whereas content analysis of trainer feedback on lesson plans, latterly revised lesson plans and online student products composed the qualitative aspect. Results revealed that this professional development training achieved significantly positive changes in teachers’ role modeling strategy implementation skills, particularly in terms of teachers’ role as agents in students’ self-regulated learning skills, promotion of student-centered learning and overall improvement in students’ self-regulated learning skills. Further, the integration of education technology tools into lessons was observed to have a positive impact on enhancing students’ self-regulated learning skills. This study could offer major contributions to designing teacher professional development training for researchers, practitioners, and teacher trainers, particularly in role modeling dimension of self-regulated learning.

Foreword ( Wilbert J. McKeachie). 1. Introduction: Self-Regulation of Learning in Postsecondary Education (Hefer Bembenutty) The chapter introduces this volume on self-regulation of learning and highlights the current trends on self-regulation presented by each of the authors. 2. Purpose of Engagement in Academic Self-Regulation (Einat Lichtinger, Avi Kaplan) This chapter argues that self-regulated learning is not a unitary construct, with students different purposes of engagement in the task meaningfully distinguishing between different types of self-regulation. 3. Self-Regulation and Achievement Goals in the College Classroom (Akane Zusho, Kelcey Edwards) This chapter links self-regulation of learning with achievement goal theory and offers practical tips to educators who struggle with disinterested learners. 4. Understanding and Facilitating Self-Regulated Help Seeking (Stuart A. Karabenick, Myron H. Dembo) The authors describe interventions to develop the competencies and resources that facilitate student help seeking as an effective selfregulated learning strategy. 5. Self-Regulation and Learning Strategies (Claire Ellen Weinstein, Taylor W. Acee, JaeHak Jung) This chapter reviews research on learning strategies, describes a model of strategic and self-regulated learning, and reports on instructional methods, interventions, and assessments that instructors can use to help students develop lifelong learning strategies they need to succeed in college. 6. Academic Delay of Gratifi cation and Academic Achievement (Hefer Bembenutty) This chapter provides a review of research on delay of gratifi cation and suggests ways in which educators can instill in students to delay gratifi cation. 7. Resistance and Disidentifi cation in Refl ective Practice with Preservice Teaching Interns (Michael Middleton, Eleanor Abrams, Jayson Seaman) This chapter examines case studies to identify contextual factors in teacher education programs that promote or inhibit teaching interns' self-refl ective practices. 8. Professional Development Needs and Practices Among Educators and School Psychologists (Timothy J. Cleary) This chapter summarizes research illustrating the importance and need for motivation and self-regulation professional development training for teachers and school psychologists across assessment, intervention, and instructional activities. 9. Transitioning from College Classroom to Teaching Career: Self-Regulation in Prospective Teachers (Judi Randi, Lyn Corno, Elisabeth Johnson) This chapter explores how preservice teachers prepare for the transition from college classroom to career through assignments and features of the learning environment designed to approximate the demands of work settings and job-related tasks. 10. The Role of Web 2.0 Technologies in Self-Regulated Learning (Anastasia Kitsantas, Nada Dabbagh) This chapter demonstrates how Web 2.0 technologies can be used to facilitate self-regulated learning in postsecondary education. The authors show how instructors can integrate social software into course design to promote students self-regulation of learning. 11. Self-Regulation of Learning with Computer-Based Learning Environments (Jeffrey A. Greene, Daniel C. Moos, Roger Azevedo) This chapter outlines how self-regulated learning skills can facilitate learning with computer-based learning environments and how educators can diagnose and build on students' self-regulated learning ability. 12. New Directions for Self-Regulation of Learning in Postsecondary Education (Hefer Bembenutty) This chapter puts into context the major contributions of this volume on self-regulation of learning and provides new directions for its promotion in postsecondary education. INDEX.

Assessment has several advantages like involving students in learning and making them cognizant of their strengths and weaknesses. The effects of peer assessment and self-assessment as two main kinds of assessment have not examined on EFL learners’ self-regulated learning, critical thinking, and problem-solving skills; therefore, the present research attempted to inspect the impacts of self and peer assessment activities on self-regulated learning, critical thinking, and problem-solving skills of Iranian EFL learners. To do so, 75 Iranian EFL learners were selected and divided into two experimental groups (peer assessment group (PAG) and self-assessment group (SAG)) and one control group (CG). Then, three questionnaires of self-regulated learning, critical thinking, and problem-solving skills were administered to the students as the pre-tests of the study. After that, one experimental group received the treatment via using self-assessment and the other experimental group received the instruction through peer assessment. The control group received a teacher-based assessment instruction. After teaching 13 English conversations to all groups, 3 post-tests were given to them to measure the impacts of the treatment on their self-regulated learning, critical thinking, and problem-solving skills. The results of one-way ANOVA showed that there was a substantial difference between the post-tests of the experimental groups and the control group. The results showed that both experimental groups outperformed the control group in the post-tests of self-regulated learning, critical thinking, and problem-solving skills. Furthermore, the outcomes revealed that there were no significant differences between the post-tests of the experimental groups. It can be concluded that both types of assessments play a vital role in English language teaching and learning. Based on the results of this study, language teachers, materials developers, and education authorities can concentrate on using self and peer assessments as one of the main strategies to develop the language learning ability of Iranian EFL learners.

Researchers, especially in the field of educational psychology, have argued that self-efficacy plays an important role in self-regulated learning. As such, teaching of self-regulated learning often focuses on enhancing self-efficacy. However, few studies have examined how the process of self-regulated learning might lead to the enhancement of self-efficacy. Therefore, the aim of this study was to investigate the effects of the self-regulated vocabulary learning process on self-efficacy. A total of 303 learners of English as a Foreign Language from two universities participated in the study. They completed a questionnaire measuring the process of self-regulated learning (i.e. forethought, performance or volitional control, and self-reflection). They also completed a vocabulary test as a measure of learning outcome. Correlation analysis was employed to evaluate the relationships between various variables investigated in the study. The results showed that self-regulated learning process can boost self-efficacy and increase vocabulary knowledge. The pedagogical implications of the current study are discussed mainly in terms of incorporating instructions aimed at enhancing self-efficacy and self-regulation in vocabulary teaching.

This study investigates secondary education students' self-regulated learning (SRL) processes with digital trace data, particularly whether SRL processes found in secondary education are comparable to those observed in higher education. We therefore adapted a digital learning environment and rule-based AI algorithm originally designed to measure SRL in higher education and collected multi-trace data from 13-year-old students ( N = 179) across three European countries during an essay-writing task. Hidden Markov modeling was employed to capture latent SRL processes. Four latent SRL processes emerged: orientation, first-reading, writing, and re-reading combined with monitoring. By clustering sequences of these latent SRL processes, we identified four sequential patterns of SRL processes at the task level: writing with metacognitive monitoring, writing intensively, reading first, writing next, and reading and writing simultaneously. Our findings highlight how AI and multi-trace data can be used to measure SRL during learning, providing a basis for enhancing personalized support. Self-regulated learning (SRL) is vital in the digital world. In this study, we investigated secondary education students' SRL processes with digital trace data. We also demonstrated that the instrumentation of a digital learning environment and rule-based AI algorithm originally designed to measure SRL processes in higher education can be leveraged to measure SRL processes in secondary education students. The real-time measurement of covert SRL processes is important as this information can 1) raise students' awareness on their learning, 2) help teachers to support students' learning, and 3) form the basis for providing personalized support for these processes with the help of AI-enhanced learning technologies. • Collected multi-trace data from 13-year-old students during an essay-writing task. • Found four SRL processes: orientation, reading, writing, re-reading with monitoring. • Identified four sequential patterns of SRL processes at the task level. • Students' task knowledge was associated with SRL at the task level.

The goal of this study was to develop and test an intervention in order to improve academic writing and SRL skills of English learners (ELs). ELs are well-represented across university and college campuses in the United States. While most of them thrive academically and receive their undergraduate and graduate degrees, a majority of ELs experience difficulties with academic writing such as limited English proficiency levels and opportunities to practice academic writing. Therefore, there is a need to develop and examine evidence-based interventions to promote the development of academic writing skills of ELs. One promising line of research involves adding instruction in self-regulated learning (SRL) to writing courses. In this study, the SRL writing intervention was delivered as a one-credit semester-long course taught at a medium research university. A mixed-methods research design, combining single case quasi-experimental design to collect quantitative data and focus group interviews to collect qualitative data, was used with undergraduate ELs (n = 8) from Southeast Asia. The results of this study revealed that the SRL writing intervention had a small positive effect on the quality of students’ persuasive writing skills, but no effect on students’ SRL skills. Focus group interviews suggested that students appreciated learning about SRL skills, but found the SRL journal confusing and frequent. These findings suggest that both writing and SRL skills are teachable, but may require more time and adjustments to the teaching and learning methods employed in the study. Recommendations for the development of the improved intervention are also provided.

Self‐regulated learning (SRL) is an active process involving multiple interacting components that evolve over time, exhibiting characteristics of complex systems such as non‐linearity, emergent behaviour, self‐organization, and hierarchy. These interactions unfold at different temporal levels, each warranting a dedicated lens to capture their distinct dynamics. In this study, we apply a complex dynamic systems lens to analyse the longitudinal dynamics of SRL. We map how different SRL processes interact with each other across time and scales: (1) the stable between‐person level, which represents the dominant approach to learning or roughly the trait of SRL, (2) the contemporaneous level, which maps how SRL processes influence each other within the same time and (3) the temporal level, which captures how processes predict or influence each other in the future. Data were collected through a weekly survey administered over 4 weeks in five courses at two institutions, complemented by LMS behavioural engagement data. A panel vector autoregression model was employed to examine the structure and dynamics of SRL and LMS behavioural engagement at the three levels. The findings suggest that central SRL processes, such as planning and adapting, take place in separate stages, in accordance with the classic SRL models, whereas other processes, like effort regulation, are more pervasive, co‐occurring with most other regulatory processes. At the aggregate level, adjusting was the most central process that drove students' SRL. As such, our results align with the main characteristics of complex systems, including non‐linearity and hierarchy. These findings have implications for the design of SRL interventions, where effort can benefit from real‐time prompts, whereas metacognitive processes might require long‐term scaffolding. Furthermore, the weak association between LMS engagement and SRL processes across all levels highlights the limitations of relying solely on behavioural trace data to infer regulation. Practitioner notes What is already known about this topic? Self‐regulated learning (SRL) is an important driver of academic success and can be influenced through targeted interventions. Most SRL research is based on group‐level data, often using static, cross‐sectional designs that overlook temporal dynamics. Recent work has highlighted that SRL can and should be modelled as a complex dynamic system. What this paper adds? There is evidence of complex systems characteristics in SRL such as hierarchy, non‐linearity and feedback loops. SRL processes follow distinct temporal phases, with some processes persisting throughout all phases. Metacognition is the most central process at the between‐person level, whereas effort is central at the within‐person level. LMS behavioural data is weakly linked to self‐reported SRL. Implications for practice and/or policy SRL interventions should consider how regulatory processes unfold over time, rather than treating SRL as a static trait. Interventions targeting effort regulation and metacognition have the potential to be the most consequential. Caution must be exerted when using average or between‐person data to inform individualized support. LMS metrics should be interpreted with care and ideally complemented by self‐report or observational data.

BackgroundLifelong learning is integral to providing safe and effective healthcare. This requires effective strategies for self-regulated learning (SRL). Problem-based learning (PBL) is one recognized method for fostering SRL skills. While self-assessment is known to promote SRL, its effectiveness within PBL tutorials, especially for new medical students, remains underexplored. Given the established evidence of self-assessment’s impact on SRL, this study examines its role specifically within PBL to explore whether it enhances self-regulatory processes in novice learners.MethodsUsing a post-positivist approach, a multi-method study was conducted, with Zimmerman’s SRL framework as a theoretical lens. A correlation analysis assessed the relationship between self-assessment and SRL. A pre-test post-test interventional study without a control group measured changes in SRL following implementation of self-assessment. Hierarchical multiple regression analysis was conducted to assess whether self-assessment predict students’ self-regulated learning improvement. The intervention used a previously validated tool the “Self-assessment Scale for Active learning and Critical Thinking (SSACT).” Additionally, qualitative methods explored the impact of self-assessment on SRL skills in the PBL tutorial context.ResultsOur findings indicate a positive correlation between self-assessment and SRL, suggesting a potential dynamic relationship between the two constructs. The students’ motivation after implementation of self-assessment is significantly increased. Self-assessment played a crucial role on the development of students’ self-regulated learning. Qualitative analysis reveals that self-assessment contributes to heightened self-awareness, goal orientation, and effective task planning among medical students in PBL tutorials. Furthermore, the provision of external feedback and revision opportunities enhanced students’ self-regulation in the learning process.ConclusionThis study sheds light on the promising role of self-assessment in augmenting SRL skills among novice medical students within PBL settings. The findings underscore the potential of self-assessment as a valuable tool to cultivate self-regulation. By bridging the gap in understanding the impact of self-assessment on SRL within PBL, this research not only contributes valuable insights but also informs the design of effective educational interventions. The use of a validated self-assessment tool can empower medical learners to develop the crucial skill of self-regulation, thereby enhancing their overall educational experience.

In this study the researcher investigates  Thai secondary students’ experiences with a personalised blended learning (PBL) platform using Microsoft Teams (MS Teams) to enhance their English communication skills and self-regulated learning (SRL) skills. Employing an intrinsic case study method, I collect data from 19 students with A1 level Common European Framework of Reference for Languages  enrolled in the remedial English course through classroom observation field notes, learners’ reflective journals, semi-structured interviews, and MS Teams assignments integration. Through thematic analysis, the findings reveal that MS Teams features, such as Reading Progress, Immersive Reader, and interactive task-based assignments, support listening, speaking, reading, and writing skills, allowing students to practise asynchronously and receive timely, personalised feedback. Regarding SRL, MS Teams enables students to set goals, track progress, and reflect on their performance while offering flexibility through adjustable deadlines and revisitable materials. However, I note challenges such as technical limitations, variations in digital literacy, and inconsistent engagement levels. Via thematic analysis I identify recurring patterns in qualitative data, while recorded data from MS Teams Insights highlight student performance and engagement trends. In conclusion, MS Teams, when integrated into PBL, significantly enhances English communication skills and SRL behaviours, providing valuable insights for improving technology-supported language instruction in secondary education contexts.

Training interventions for self-regulated learning foster the use of strategies and skills as well as their transfer to new learning tasks. Because cognitive strategies or motivation regulation strategies are task-specific, their transfer is limited. In contrast, metacognitive skills are task-general and transferable to a wide variety of learning tasks. Questions arise, therefore, as to whether students transfer metacognitive skills spontaneously and how to support metacognitive skill transfer. Previous research shows that hybrid training, which addresses both metacognitive skills and cognitive strategies, supports near transfer. However, it is not clear whether hybrid training also fosters far transfer of metacognitive skills. In investigating this research question, 233 fifth-grade students were randomly assigned to six different conditions: two hybrid-training conditions (metacognitive skills and one out of two cognitive strategies), two non-hybrid training conditions (“only” one out of two cognitive strategies), and two control training conditions (neither metacognitive skills nor cognitive strategies). After 15 weeks of training, transfer of metacognitive skills to learning tasks similar to training tasks (near transfer) was tested. In the following 15 weeks, all students received a second, non-hybrid training involving a new cognitive strategy. Far transfer of metacognitive skills to the new cognitive strategy was tested afterward. The results show that hybrid training, compared to non-hybrid and control training, improved both students’ near and far transfer of metacognitive skills. Moreover, cognitive strategy use increased in at least one of the hybrid-training conditions. However, since the level of metacognitive skills use remained low, further means to support transfer are discussed.