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Background: For engineering students, a lack of motivation and continuous study are common issues that lie in low academic performance. Active teaching with audio‐visual systems, on the one hand, and self‐regulated learning methodologies, on the other, have shown to have a high potential in these aspects. Purpose: Assessing a proposal based on a self‐assessment and integrating it into a traditional teaching process to improve student engagement and performance. Design/Method: When once explanation of a thematic block was complete, we set a series of exercises encompassing key concepts for students to solve at home within a limited time. Students then had to upload their solutions to an e‐Learning platform and subsequently received dynamic videos, created using a lightboard studio, showing solutions to the exercises to assess their level of learning through self‐evaluation. Results: The activity was highly valued by the students. They were more motivated in their studies than the control group, which is reflected in increased participation in the course and in the number of students who sat for the exams. However, according to the metrics of the videos and their responses to the questionnaires, students did not fully utilise the available resources. This is likely due to the extrinsic motivation facilitated or failure to treat the self‐assessments as exam simulations. This resulted in academic performance that is very similar to that of the control group. Conclusions: The results obtained demonstrate the usefulness of the teaching proposal for the purpose of this work, although it requires some improvements. [ABSTRACT FROM AUTHOR]

The effect of technology on primary students’ self-regulated vocabulary learning (SRVL) over time and its dynamic relationship with vocabulary outcomes have been scarcely studied. This quasi-experimental study reports a longitudinal inquiry into the effect of a mobile-assisted self-regulation scheme on primary students’ SRVL and the relationship between the changes in the perceived SRVL skills and vocabulary learning outcome. The study lasted seven months. Participants were 174 Grade 4 students (89 girls) from four classes at a primary school in Mainland China. Two classes were randomly assigned to the experimental and control groups. Students in both groups used the app named Vocab+, the former with and the latter without a mobile-assisted self-regulation scheme. Data collection included questionnaires on students’ perceived SRVL skills and vocabulary tests. Latent Growth Modelling (LGM) was used to analyse data. The results showed that perceived SRVL skills and vocabulary learning outcomes increased over time. The findings further revealed that students in the experimental group exhibited a steeper increasing trend in perceived SRVL skills and vocabulary learning outcomes. Besides, the association between the growth rates of students’ perception of SRVL skills and vocabulary learning outcomes was stronger with the experimental group than with the control group. Our results provided theoretical implications for understanding the relationship between SRVL skills and vocabulary learning outcomes from a developmental perspective.

The study addressed the influence of self-regulated learning (SRL) in English language learning. It involved 23 high school students attending a private school in Surabaya. The school implements bilingual language usage, incorporating both English and Indonesian. Therefore, most of the students demonstrated high fluency in English, as evidenced by their effortless communication during class activities. The students completed a scale and open-ended questionnaire regarding self-regulated learning and participated in an English proficiency test. The data were analysed using simple regression analysis. The finding suggests that self-regulated learning did not predict students’ English proficiency. Instead, according to students’ openended responses, the study found that students’ English proficiency was highly influenced by their exposure to the language naturally without structured learning strategies. Future studies should explore a more thorough assessment of students’ self-regulated learning levels and their connection with English proficiency, particularly in similar contexts. [ABSTRACT FROM AUTHOR]

A core focus of self‐regulated learning (SRL) research lies in uncovering methods to empower learners within digital learning environments. As digital technologies continue to evolve during the current hype of artificial intelligence (AI) in education, the theoretical, empirical and methodological nuances to support SRL are emerging and offering new ways for adaptive support and guidance for learners. Such affordances offer a unique opportunity for personalised learning experiences, including adaptive interventions. Exploring the application of adaptivity to enhance SRL is an important and emerging area of research that requires further attention. This editorial introduces the contributions of seven papers for the special section on adaptive support for SRL within digital learning environments. These papers explore various themes related to enhancing SRL strategies through technological interventions, offering valuable insights and paving the way for future advancements in this dynamic area. [ABSTRACT FROM AUTHOR]

The motivational basis of self-regulated learning lays a solid theoretical framework for education researchers to look closely at the learners' intrinsic motivational factors in enhancing their academic outcomes. Particularly, learners' motivation forces, embedded in the self-regulatory learning (SRL) process, have not been well researched in an online learning environment, yet the correlations to learners' academic success. Hence, the current study employed 713 online university students and focussed on the motivational path rooted in the SRL model to elucidate the extent to which learners' motivational forces contribute to academic achievements. The results indicated that learning goal orientation was positively correlated to academic outcomes, while this correlation was not found to be mediated by academic self-efficacy, engagement, and learning satisfaction in an online learning environment. Further, the correlation between learning goal orientation and learning satisfaction was found to be mediated by academic self-efficacy and learning engagement. Directions for future research on the motivational bases of self-regulated learning are discussed. [ABSTRACT FROM AUTHOR]

The process of academic writing is a highly demanding mental activity that presents a number of difficulties for students, especially when it comes to L2/FL (second/ foreign language) writing. The study employs the social-cognitive model of writing to explore the issue of students’ self-regulated learning (SRL) in English as a foreign language (EFL) writing, with a special emphasis on the most important processes and strategies that may influence the quality of writing performance. We also wanted to explore whether there is an improvement in the quality of writing performance due to regular students’ exposure to EFL learning at the university levels. The quantitative part of the study involved 104 students (53 undergraduates and 51 graduates), while the qualitative part focused on two groups of higher and lower proficiency writers. The quantitative part of the study pointed out a significant difference between the first and second measurement points in the quality of students’ writing performance both at the undergraduate and graduate levels of study. Students in second measurement point had a better writing performance compared to the ones in the first measurement point. The qualitative research results showed that higher proficiency writers exhibited better SRL processes compared to lower proficiency writers. The research findings suggest that the students’ writing proficiency benefits from incorporating more SRL processes in EFL learning/teaching in the Croatian educational context.

This article, titled "Editorial: Beyond cognition - adaptive technology for individualized learning," discusses the use of adaptive technology in personalized learning. The article highlights the increasing prevalence of artificial intelligence (AI) applications and immersive technologies, such as virtual reality (VR), in adapting the learning process to individual learners' abilities, motivation, and preferences. The article emphasizes the importance of considering a range of learner characteristics, including cognitive, metacognitive, motivational/affective, and social factors. The article presents four studies that explore learner motivation and self-regulated learning in the context of adaptive technology-supported learning. These studies demonstrate the potential of immersive technologies, AI-supported learning, and adaptive scaffolding to enhance learning experiences and improve learning outcomes. The article concludes by emphasizing the need to incorporate innovative approaches and technologies to improve individualized learning experiences and educational processes. [Extracted from the article]

It is emphasized in the Self-regulated learning (SRL) framework that self-monitoring of learning state is vital for students to keep effective in studying. However, it's still challenging to get an accurate and timely understanding of their learning states during classes. In this study, we propose to use electrodermal activity (EDA) signals which are deemed to be associated with physiological arousal state to predict the college student's classroom performance. Twenty college students were recruited to attend eight lectures in the classroom, during which their EDA signals were recorded simultaneously. For each lecture, the students should complete pre- and after-class tests, and a self-reported scale (SRS) on their learning experience. EDA indices were extracted from both time and frequency domains, and they were furtherly mapped to the student's learning efficiency. As a result, the indices relevant to the dynamic changes of EDA had significant positive correlations with the learning efficiency. Furthermore, compared with only using SRS, a combination with EDA indices had significantly higher accuracy in predicting the learning efficiency. In conclusion, our findings demonstrate that the EDA dynamics are sensitive to the changes in learning efficiency, suggesting a promising approach to predicting the classroom performance of college students. [ABSTRACT FROM AUTHOR]

This study focused on the implementation of case-based teaching videos on e-learning platform and the effect of these videos on the self-regulated learning outcomes of students in a community work course. The purpose of this study was to explore the relationship between students’ learning behaviors and self-regulated learning and the effect of students’ self-regulated learning on their learning performance. This study employed a pre-experiment and a single-group, posttest design with a 4-month research period. The research participants were 44 social work students of a community work course at a university in Taiwan. The results of this study indicated that in self-regulated learning, case-based teaching videos had a positive effect on the learning motivation of all students and the information processing of students who achieved high scores in the final exam. Viewing case-based teaching videos enhanced the students’ academic performance. When the videos matched the personal experience of and aroused empathy among the students, their learning motivation increased. Academic performance improved when the videos were linked to practical experience, clarified confusing concepts, and could be watched multiple times. Discussions and suggestions regarding the design of case-based teaching videos and the relationship between students’ learning behaviors and self-regulated learning are presented. [ABSTRACT FROM AUTHOR]

This paper explores international students' engagement with educational technology for self-regulated English learning at an Australian university. Despite the increased use of automated feedback systems (AFSs) for language assessment, students' critical engagement with them for independent learning remains under-researched. The study primarily employed a qualitative approach to understand the students' preferred AFS tools and critical engagement throughout their personalised learning journeys but it also included a small-scale quantitative component. Data were gathered from seven students' eportfolios, focus group interviews as well as a survey among 32 participants. Results highlight positive perceptions and successful use of AFSs, with students leveraging these tools to identify improvement areas, track progress and gain confidence. The study emphasises the importance of course structure, teacher guidance and a combination of human and automated feedback, in fostering learner autonomy and emotional selfregulation. The paper underscores the potential for sustained use of AFSs beyond the cours, and the significance of guiding learners to critically use these tools for ongoing learning and growth rather than dependence. These findings have significant implications, as readily available artificial intelligence tools such as ChatGPT hold great pedagogical potential for self-regulated learning within and beyond the language learning field. [ABSTRACT FROM AUTHOR]

Conceptualized in formative assessment and sociocognitive theory, peer feedback and self-regulated learning (SRL) instruction were used in this mixed-method study to investigate their effects on Thai EFL university students' essay writing ability and their self-regulation. During the 12-week online instruction period, 35 third-year students majoring in Business English at a public university were taught essay writing using the integration of peer feedback activities and SRL. An essay writing test, a self-regulation questionnaire, and semistructured interviews were used to collect data. Findings revealed that students' essay writing ability and self-regulation had significantly improved after the intervention. Our findings shed light on the feasibility and necessity incorporating the interdisciplinary dimensions of education such as instruction, assessment, and social-cognitive theory, in enhancing learners' academic performance and their lifelong learning strategies. Our findings also suggest that students can be trained in peer feedback and SRL strategies via online platforms, which has implications for the continuing tendency towards online instruction in the post-pandemic era. Pedagogical implications are also provided to help teachers improve their students' writing performance and self-regulation. [ABSTRACT FROM AUTHOR]

AbstractSelf-regulated learning (SRL) has been promoted as playing a key role in proactive, life-long learning. The present study aimed to investigate the effect of different types of teacher feedback on students’ self-regulated learning (SRL) in a special educational needs (SEN) context. It employed a mixed method, quasi-experimental with repeated-measures pre-test-treatment-post-test design. Forty-five students from a SEN school were explicitly taught SRL strategies over nine sessions. Participants were divided into two matched groups and provided different types of feedback (DF group) or corrective feedback only (CF group). Data was collected from individual interviews and student artefacts. Consistent with research on the benefits of explicit SRL instruction in mainstream school contexts, this study in the SEN context found statistically significantly higher student SRL scores at post-test than pre-test. Comparing scores between the feedback groups turned out not statistically significant. However, insightful qualitative differences were found in analyses of assignments and interview data at all three phases of SRL. Findings coalesced around the themes of Skill and Will, providing insights to students’ motivation and affect, influencing student volition. These findings suggest both changes at the practice and policy level in SEN contexts to bring about feedback-rich learning environments to facilitate SRL.

An 8-week voice regulation training program (VRTP) incorporating everyday activities was implemented in an experimental preschool classroom (EG; n = 34), which was compared with a control preschool classroom (CG; n = 31). The VRTP includes songs, games, and conversations aiming to raise children's awareness of noise levels and teach voice modulation skills. Grounded in the theoretical framework of self-regulated learning, the study's objectives were to evaluate the impact of the VRTP on noise levels, children's self-regulation, and pre-literacy skills. Noise levels were assessed weekly using an electronic noise meter before and during the program. The EG preschoolers demonstrated modest but significant improvements over their pre-VRTP levels of voice modulation, behavioral and emotional self-regulated learning, and pre-literacy skills, in contrast with the CG children. The findings provide evidence that young children's self-regulation may be enhanced in preschool, challenging the field of developmental-educational psychology to consider self-regulated learning during early childhood. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to examine the factors that contribute to the early prediction of Massive Open Online Courses (MOOCs) dropouts in order to identify and support at-risk students. We utilize MOOC data of specific duration, with a guided study pace. The dataset exhibits class imbalance, and we apply oversampling techniques to ensure data balancing and unbiased prediction. We examine the predictive performance of five classic classification machine learning (ML) algorithms under four different oversampling techniques and various evaluation metrics. Additionally, we explore the influence of self-reported self-regulated learning (SRL) data provided by students and various other prominent features of MOOCs as potential indicators of early stage dropout prediction. The research questions focus on (1) the performance of the classic classification ML models using various evaluation metrics before and after different methods of oversampling, (2) which self-reported data may constitute crucial predictors for dropout propensity, and (3) the effect of the SRL factor on the dropout prediction performance. The main conclusions are: (1) prominent predictors, including employment status, frequency of chat tool usage, prior subject-related experiences, gender, education, and willingness to participate, exhibit remarkable efficacy in achieving high to excellent recall performance, particularly when specific combinations of algorithms and oversampling methods are applied, (2) self-reported SRL factor, combined with easily provided/self-reported features, performed well as a predictor in terms of recall when LR and SVM algorithms were employed, (3) it is crucial to test diverse machine learning algorithms and oversampling methods in predictive modeling. [ABSTRACT FROM AUTHOR]

An 8-week voice regulation training program (VRTP) incorporating everyday activities was implemented in an experimental preschool classroom (EG; n = 34), which was compared with a control preschool classroom (CG; n = 31). The VRTP includes songs, games, and conversations aiming to raise children's awareness of noise levels and teach voice modulation skills. Grounded in the theoretical framework of self-regulated learning, the study's objectives were to evaluate the impact of the VRTP on noise levels, children's self-regulation, and pre-literacy skills. Noise levels were assessed weekly using an electronic noise meter before and during the program. The EG preschoolers demonstrated modest but significant improvements over their pre-VRTP levels of voice modulation, behavioral and emotional self-regulated learning, and pre-literacy skills, in contrast with the CG children. The findings provide evidence that young children's self-regulation may be enhanced in preschool, challenging the field of developmental–educational psychology to consider self-regulated learning during early childhood.

This study aims to underline the importance of school-based social-emotional learning (SEL) by exploring the relationship between self-regulated learning (SRL) strategies and science achievement with a moderator of students' emotional skills. In previous studies, SEL scholars have paid attention to explaining the complicated relationships among the social, emotional, and cognitive development of school-aged children. Based on the SEL framework, this study investigated the moderating effect of emotional skills on students' SRL strategies and science achievement with 79 sixth-grade students in South Korea. Students' emotional regulation was a significant moderator of all the subfactors in SRL and science performance. Notably, motivational beliefs in SRL strategies are linked to higher science achievement. The findings support the idea of a SEL approach that posits that social and emotional variables are related to students' science achievement, which invites the consideration of how these emotional skills can assist students to become better prepared learners. [ABSTRACT FROM AUTHOR]

The rapid development of mobile technologies and their price decrease have enabled mobile devices to become ubiquitous. Both lecturers and students are integrating mobile technologies into teaching and learning. The continuous global innovation in emerging mobile technologies and their ever-increasing overlap with the lives of students and lecturers in Higher Education Institutions (HEIs) have thrust Mlearning and self-regulated learning into prominence. Accordingly, this review analyses conference proceedings and national and international journals on the potential of M-learning for fostering selfregulated learning. To select relevant sources, a systematic literature review approach was employed. This study fills gaps in existing literature and investigates how mobile devices might enhance self-regulated learning among university students. It also signals future research directions and offers implications for researchers and practitioners in HEIs. [ABSTRACT FROM AUTHOR]

As online learning becomes a major development in recent years and escalates due to the COVID-19 pandemic, it helps to have a high self-efficacy and self-regulated learning (SRL) to succeed in such a learning context. This study explored the undergraduates' levels of self-efficacy and SRL and provides a comparative analysis of these variables while learning Arabic as a Foreign language via online. The data was collected from 77 undergraduates in a public university in Malaysia through an online survey. The findings showed that both self-efficacy and SRL mean scores were high and that there was a statistically strong positive relationship between self-efficacy and SRL. Students appeared to adapt to online learning by managing their time, organising their schedules, interacting with classmates and instructors, and selecting the best spot to maximise their online learning experience. The findings suggested that it is important and beneficial for language instructors to create interesting and inspiring lesson plans in an online environment so that the undergraduates could experience satisfaction inside and outside of learning, and simultaneously facilitate them for their success in foreign language learning. [ABSTRACT FROM AUTHOR]

In recent years, a considerable body of empirical research has acknowledged the role of self-regulated learning (henceforth SRL) in the domain of English as a foreign language (EFL). However, the study investigating the role and mechanism of SRL in vocabulary learning is still in scarcity particularly in Indonesian contexts. To address this noticeable gap, this multi-case study aims to explore the role of SRL on vocabulary learning strategies use and mechanism from the experience of undergraduate EFL learners. After signing the informed of consent form sheets, two undergraduate students from two different countries (Indonesia and Egypt) voluntarily participate in this study. By employing a series of semi-structured interviews and conducting narrative thematic analysis (Braun Clarke, 2006), the findings showcase that both participants employ a myriad of vocabulary learning strategies such as rehearsal, elaboration, and social strategy. Additionally, the empirical evidence indicates that they have higher level of motivation and persistence to maintain vocabulary-learning activity. The findings suggest the important practical implications for teachers, learners, and institution. This article also discusses limitations and recommendations.

Abstract The present study explored the impact of mobile-assisted self-regulated learning (SRL) on developing university students’ knowledge of academic vocabulary in English. The participants were 49 students in experimental (N = 28) and control (N = 21) learning conditions. Those in the experimental group studied 70 academic words using digital flashcards application installed on their mobile devices (i.e., smartphones), and the control group learned the same words using traditional materials (i.e., word lists). The participants’ vocabulary knowledge was tested before and after the treatment, and their test scores were analyzed using mixed between-within-subjects analysis of variance (ANOVA). The findings indicated a significant main effect for time in both SRL interventions, as both strategies were effective in scaffolding university students’ academic vocabulary development, and the learning gains were significant in post- and delayed post-tests. Additionally, the findings revealed a significant main effect for mobile-assisted SRL in that participants in the experimental group outperformed those in the control group on post-treatment tests. Accordingly, the results provide empirical evidence for the effectiveness of mobile-assisted vocabulary learning in the SRL mode. The study offers implications for addressing the academic vocabulary learning needs of English as a Foreign Language (EFL) university students.

There is widespread agreement that student teachers need to construct an integrated knowledge base across multiple domains. This study examined the contributions of intraindividual factors of self-regulated learning to explaining student teachers' (a) integration of knowledge across topics and domains (i.e., integrative learning) and (b) disjointed processing of potentially domain-specific learning content (i.e., separative learning). The factors considered were study approaches; cognitive, metacognitive, and resource-related learning strategy use; epistemological and pedagogical beliefs; and career choice motivation. The study applied a cross-sectional survey design and examined separative and integrative learning in N = 103 student teachers by way of multiple regression analyses with backward eliminations. A key finding is that deep and strategic study approaches and certain cognitive learning strategies contributed significantly to explaining integrative learning in student teachers. Epistemological and pedagogical beliefs were not able to predict integrative learning. Regarding separative learning, the study identified the surface study approach, specific epistemological and pedagogical beliefs, and the "usefulness" motive for career choice as positive predictors and critical thinking as a negative predictor. The study demonstrates differences in how integrative and separative learning are shaped by distinct intraindividual factors. Implications are discussed with regard to student teachers' self-regulated learning and pre-service teacher education. [ABSTRACT FROM AUTHOR]

Academic writing is a complex and demanding activity in which students have to regulate their (meta)cognitive, motivational, and linguistic processes and self-regulatory writing strategies might serve as a tool to accomplish writing tasks. The research was done as part of a verification of Zimmerman & Risemberg’s (1997) model of self-regulation in writing. Previous research on the relationships between students’ self-regulated learning (SRL) and writing performance has suggested their positive impact. Therefore, this paper attempts to provide insights into Croatian university students’ first/second language (L1/L2) writing performance regarding the SRL strategy use. Students’ written performance in both L1 (Croatian) and L2 (English) was checked, and the contributions of SRL and sociodemographic factors were explored. A total of 104 students from the initial and final years of teacher education study were included in the research. A quantitative research method was used including the following instruments: The learning orientation scale, the Perceived academic control scale, the Croatian version of the values subscale, Writing strategies questionnaire. Descriptive analyses revealed that students’L1/L2 writing proficiency was on average. There was no difference between L1 and L2 writing proficiency. Furthermore, the study showed that students mostly initiated learning goal orientation, writing tasks were valuable to them and they had more results of academic control over the mentioned tasks. Participants mostly used the most effective writing strategy - checking and correcting the text. The final study year students had better L1 writing proficiency compared to the initial study year students. Such results were expected since students were exposed to the extensive L1 academic experience, which was not the case with the exposure to learning English as a foreign language (EFL learning), resulting in a lower level of L2 essay writing proficiency. Success in L1 writing proficiency was explained more by cognitive and less by sociodemographic and motivational factors. The greater academic control over writing assignments and the lower goal orientation on avoiding effort was shown, the greater success was achieved. Success in L2 writing proficiency was mostly explained by cognitive factors, but also significantly by some sociodemographic and motivational factors. The higher GPA in L2 and the less asking for help and writing by the model strategy was employed, the greater success in writing assignments was achieved. The study indicated the importance of mastering SRL, especially cognitive factors in both L1 and L2 learning. The implications of the study were discussed which may benefit L1/L2 teachers to teach their students SRL writing strategies by which students could self-regulate their thoughts, feelings, and behaviours throughout the writing process to achieve academic success.

Collaborative writing (CW) is a pedagogical practice that requires active engagement from all participants to create more L2 learning opportunities, which help to develop metacognitive awareness and writing autonomy. In self-regulated learning research, learners apply various regulated learning (RL) strategies to monitor their individual process within a task. These same RL strategies can be applied to the co-regulatory processes of CW, but to regulate themselves, their partners and/or social group at different co-construction stages (Hadwin & Miller, 2017). While current CW research highlights L2 development benefits, less is known about how pairs with collaborative orientations use RL strategies during co-regulatory processes. To fill this gap, this study aims to identify the RL strategies that students with collaborative orientations use to maintain their collaborative patterns of interaction. Through a Sociocultural Theory perspective, the transcribed audio recordings of six international postgraduate students during two CW activities were examined using languaging episodes as the basic unit of analysis before coding each episode for RL strategies and three regulatory agents. The findings revealed how pairs used varied RL strategies when addressing local and/or global issues to maintain collaborative patterns. They were able to appropriate some knowledge from the first CW activity to the second by applying various RL strategies to improve on time management and writing efficiency. Understanding the dynamic co-regulatory process sheds additional light on how RL strategies can be appropriated as conceptual knowledge to co-writing collaboratively. • Co-regulation in CW includes dynamic, temporal shifts between regulatory agents. • Pairs used varied Regulated Learning (RL) strategies according to their goals and pair dynamics. • Some RL strategies were appropriated and applied to second CW to address issues related to time constraints and composition. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to examine the factors that contribute to the early prediction of Massive Open Online Courses (MOOCs) dropouts in order to identify and support at-risk students. We utilize MOOC data of specific duration, with a guided study pace. The dataset exhibits class imbalance, and we apply oversampling techniques to ensure data balancing and unbiased prediction. We examine the predictive performance of five classic classification machine learning (ML) algorithms under four different oversampling techniques and various evaluation metrics. Additionally, we explore the influence of self-reported self-regulated learning (SRL) data provided by students and various other prominent features of MOOCs as potential indicators of early stage dropout prediction. The research questions focus on (1) the performance of the classic classification ML models using various evaluation metrics before and after different methods of oversampling, (2) which self-reported data may constitute crucial predictors for dropout propensity, and (3) the effect of the SRL factor on the dropout prediction performance. The main conclusions are: (1) prominent predictors, including employment status, frequency of chat tool usage, prior subject-related experiences, gender, education, and willingness to participate, exhibit remarkable efficacy in achieving high to excellent recall performance, particularly when specific combinations of algorithms and oversampling methods are applied, (2) self-reported SRL factor, combined with easily provided/self-reported features, performed well as a predictor in terms of recall when LR and SVM algorithms were employed, (3) it is crucial to test diverse machine learning algorithms and oversampling methods in predictive modeling.

Objective: To explore self-regulated learning strategies in high-performing undergraduate medical and dental students. Study Design: Qualitative Case study. Setting: Medical and Dental students of a Private Medical and Dental College in Karachi. Period: August 2021 to December 2021. Material & Methods: A qualitative case study using constructivist and pragmatic paradigm was done. Data was collected using semi-structured interviews of high-performing students. Thematic analysis was done using atlas ti-9 for organizing data. Microanalysis was used to collect data from high achievers in three sequential phases: Examination prepratory activities, During examination performance, and self-reflection, processes following examination. Results: It showed twenty codes under three themes, Examination prepration activities, performance, Examination attempting abilities and Reflective practices. Examination prepratory activities codes were memory strategies, organization of content, rehersals, eloboration, group discussions, imagery, goal setting,strategic planning, time management, Mindfulness, lesson plan monitoring activities, learning plan, intrinsic motivation, meta-cognition, quality sleep, co-regulatory network and procrastination. Process or performance codes identified were, self-control, self-confidence, presentation of content, Problem-solving abilities, self-instruction, time management during examination. Reflective practices codes identified were receptive to feedback, self-consequence, reflective attitude and vision. Conclusion: High- achievers have centain self-regulatory attibutes which enhance their learning experience and help them to excel. The attributes identified through the research after exploring self-regulatory attributes in high achievers can be utilized to improve abilities of all medical and dental students. [ABSTRACT FROM AUTHOR]

In involuntary distance education, like during epidemics and wars, students often feel heightened learning anxiety, impacting outcomes. Despite innovative teaching methods, many face hurdles in distance learning. We want to propose specific strategies to solve learning difficulties in distance education., Aim: This study explored whether using digital concept maps (DCM) in physiology courses can reduce learning anxiety among nursing students., Design: The study was quasi-experimental, including a pre-and post-test control group., Methods: 71 nursing students aged 16-18 enrolled in a physiology course were recruited in the study. DCM was the intervention as a tool for in-person learning (first 12 weeks) and distant learning (final six weeks). Each student was required to complete the assignments independently to compare learning outcomes. Questionnaires were administered, and an assignment evaluation was completed before and after the course's different formats., Results: DCM using software using mobile vehicles (mobile, notebook, pad) is digital learning to help nursing students learn difficult subjects. DCM improved the students' learning motivation and effectiveness more in distance learning than in-person learning, decreasing learning anxiety in both face-to-face and distance learning., Conclusions: DCM promoted students' self-regulated learning and positively affected learning outcomes by increasing motivation and reducing stress. This study offers a tailored teaching framework for international settings to reduce student anxiety and improve learning effectiveness., Competing Interests: Declaration of Competing Interest There are no conflicts of interest., (Copyright © 2024. Published by Elsevier Ltd.)

Teachers of students with disabilities have been assessed from various perspectives. This study aimed to investigate the knowledge and practice of self-regulated learning (SRL) of teachers who teach students with learning disabilities (SLD) in secondary schools in Riyadh, Saudi Arabia. The study focuses on the impact of teachers' knowledge in their practices of SRL and identified the moderating effect of teachers' gender on this impact. Using Pintirich's model of SRL, the study designed the Teachers' Knowledge of Self-Regulated Learning Scale, and it adopted Huh's Teachers' Practices Related to Developing Students' SRL questionnaire to examine teachers' knowledge and practices of SRL. The questionnaire was distributed online to over 318 Saudi teachers in secondary schools in Riyadh who were selected by using stratified sampling techniques. Teachers demonstrated high knowledge of SRL in all domains (cognition: M = 5.2, motivation: M = 5.38, behavior and emotions: M = 5.44) and medium SRL practices level in their classes (M = 3.5) with some reservation on their reaction and reflection, which were at the lowest average level. Furthermore, results revealed a direct and significant influence of teachers' knowledge on the practice of self-regulated learning (SRL) (β = 0.183, t = 3.301, p = 0.000), and there was no moderate effect of teachers' gender on the impact of teachers' SRL knowledge on teachers' SRL practices (β = −0.004, t = 0.064; p = 0.949). The results suggest the demand for more practical training programs for SLD teachers to increase their SRL application in practice. [ABSTRACT FROM AUTHOR]

Self-regulated learning (SRL) is a crucial higher-order skill required by learners of the 21st century, who will need to become lifelong learners to adapt to the continually changing environments. Literature provides examples of tools for scaffolding SRL in online environments. In this article, we provide the state-of-the-art concerning tools that support SRL in terms of theoretical models underpinning development, supported SRL processes, tool functionalities, used data and visualizations. We reviewed 42 articles published between 2008 and 2020, including information from 25 tools designed to support SRL. Our findings indicate that: 1) many of the studies do not explicitly specify the SRL theoretical model used to guide the design process of the tool; 2) goal setting, monitoring, and self-evaluation are the most prevalent SRL processes supported through functionalities, such as content navigation, user input forms, collaboration features, and recommendations; 3) the relationship between tool functionalities and SRL processes are rarely described; and 4) few tools assess the impact on learners’ SRL process and learning performance. Finally, we highlight some lessons learned that might contribute to implementing future tools that support learners’ SRL processes. [ABSTRACT FROM AUTHOR]

This study validated a scale of students’ learning satisfaction (SLS) and self-regulated learning (SRL) strategies in MOOCs to measure the relationship between SRL and SLS based on Zimmerman’s SRL theory and Piccoli’s web-based Virtual Learning Environment (VLE) effectiveness theory. The process of developing the scale included literatures review, face and content validity, pilot study, data collection, and data analysis. An online self-reporting questionnaire was designed to include constructs such as goal setting (GS), task strategy (TS), self-evaluation (SE), help-seeking (HS), environment structuring (ES), time management (TM) and students’ satisfaction (SA). All these constructs were assessed on a 5-point Likert scale. The data was collected from 333 Malaysian students in higher education, and it was analysed by using Partial Least Squares Structural Equation Modelling (PLS-SEM) technique. The resultant constructs have shown empirical result of good reliability and validity where the coefficients of Cronbach’s alpha were ranged between 0.784 to 0.877, HTMT values were passed of 0.90 tests and factors loading were more than 0.7. The resulting constructs can be used by the practitioners, academicians, researchers, and policy makers to have a clear understanding on SLS and SRL in MOOC so that, a suitable, effective, positive, and meaningful MOOC learning environment could be established in the universities, higher education learning institutions and/or training organizations. [ABSTRACT FROM AUTHOR]

Student-facing learning analytics (SFLA) hold promise for supporting the development of self-regulated learning (SRL) skills students need for academic success, especially in online learning. However, the promise of SFLA for supporting SRL is unrealized because current SFLA design methods are technocentric, with little attention to learning science theory and student needs, and there is little guidance for SFLA designers. Based on insights from literature and a survey with learning analytics (LA) experts, we have developed a framework to guide the design of SFLA. The framework is built around three questions that designers should address to generate SFLA features for supporting SRL: What are the students’ self-regulated learning support needs based on self-regulated learning theory? What are the students’ perspectives of SFLA in meeting their SRL needs? What SFLA features are appropriate to support students’ self-regulated learning based on their SRL needs? A set of activities that should be conducted to respond to each question is identified within the framework. To evaluate the framework, a focus group discussion with LA experts was conducted, and feedback obtained was used to revise the framework. The framework provides a rationale for understanding student needs as informed by theory. [ABSTRACT FROM AUTHOR]

This study explores the impact of learning analytics (LA)-based feedback on students' self-regulated learning (SRL) and academic achievement in a blended English-as-a-foreign-language (EFL) course. Employing a quasi-experimental research design, this study utilized propensity score matching (PSM) to form a treatment group (N = 160) from the 2023 undergraduate student cohort, receiving LA-based feedback, and matched it with a comparison group of equivalent size from the 2021 and 2022 cohorts without such feedback. Guided by Winne and Hadwin's COPES model (1998), SRL was operationalized at a coarse level with students' online log data and course assessment scores representing their SRL operations and products of SRL in the course, respectively. Results of mixed ANOVAs and chi-square tests of independence showed that the LA-based feedback enhanced students' completion rate of online learning activities and their study regularity. The treatment group exhibited superior performance in the final examination compared to the comparison group, providing evidence of the positive impact of LA-based feedback on students' course performance. The study represents an initial effort to utilize LA-based feedback to support students' SRL operations and course performance in an EFL context. [ABSTRACT FROM AUTHOR]

Motivation and self-regulated learning (SRL) are interrelated constructs. Motivation can be a precursor, a mediator, and an outcome of SRL. In L2 learning, the interrelatedness of motivation and self-regulation has long been recognized (Dörnyei, 2005). However, a conceptualization of the connections is lacking. This article models the L2 motivation–SRL relationship. Drawing a distinction between personal and social sources of motivation (Zimmerman & Schunk, 2008), attention is directed to variation in self-evaluation processes. With a focus on self-evaluation where social standards provide points of reference (Higgins, 1990), and drawing on a model where connections between the self-system and SRL are conceptualized at the timescale of working cognition (McCombs & Marzano, 1990), a model of the L2 motivation–SRL relationship is presented. The model identifies paths of influence relating to (i) self-evaluation focused on personal criteria, and (ii) self-evaluation where reference points are provided by social standards. The model provides a conceptual framework for systemically structured investigation, a heuristic for the interpretation of research findings, and a tool to support L2 learners' motivation and SRL. Explanations of how socially focused self-appraisal can promote proactive learning behaviours are provided. [ABSTRACT FROM AUTHOR]

Self-regulated learning includes the cognitive, metacognitive, behavioral, motivational, and affective aspects of learning. The conceptualization of self and socially regulated learning has recently received much attention and peer assessment has been found to increase the use of metacognitive activity. The present exploratory qualitative study aimed to identify self-, co-, and socially shared regulatory processes in an oral English as a Foreign Language task. The regulatory activity deployed by 10 learners was studied within the context of a peer assessment task using an assessment form paired with video feedback in the context of an English language classroom at a French university. These interactions were filmed and discussed in individual self-confrontation interviews which were analyzed through inductive coding. Specific findings from the classroom setting shed light on existing gaps in the literature. First, students can gain confidence in their own skills through assessing their peers and activating regulatory processes both individually and as a group. Second, appropriate tools can increase co-regulated and socially regulated learning through the structuring of cooperative regulatory behaviors. Third, psychological safety appeared to be a propitious social context for supporting regulated learning (SRL, CoRL, and SSRL). We also shed light on the fact that adaptive regulatory strategies are present in oral (as well as written) English as a Foreign Language tasks. These results indicate the potential for learning situations based on video feedback used in conjunction with peer assessment and collaborative learning in order to develop regulatory behaviors in language learners.

The COVID-19 pandemic introduced significant disruptions and challenges to the learning environment for many post-secondary students with many shifting entirely to remote online learning. Barriers to academic success already experienced in traditional face-to-face classes may be compounded in the online environment and exacerbated by stressors related to the pandemic. In 2020–2021, post-secondary institutions were faced with the reality of rolling out fully online instruction with limited access to resources for assisting students in this transition. Instructional interventions that target students’ ability to self-regulate their learning have been shown to improve academic performance and self-regulated learning (SRL) competencies have also been found to mediate the effect of SRL interventions on higher education. However, few studies have examined the efficacy of fully online SRL intervention on mitigating the impact of psychological distress and academic challenges on academic success. This study examined the moderating roles of self-regulatory practices and SRL intervention in buffering the influence of COVID-related psychological distress and academic challenges on academic outcomes (self-reported grade point average (GPA) and academic challenges) in a Canadian sample of undergraduate students (n = 496). We found (a) levels of metacognitive and motivational challenges fully mediated the impact of COVID distress on GPA, (b) SRL adapting practices moderated the impact of metacognitive challenges on GPA, and (c) semester-long SRL intervention buffered the impact of COVID distress on academic challenges and resulted in lower levels of social-emotional, cognitive, and metacognitive challenges for first year undergraduate students.

Social network services such as Twitter are important venues that can be used as rich data sources to mine public opinions about various topics. In this study, we used Twitter to collect data on one of the most growing theories in education, namely Self-Regulated Learning (SRL) and carry out further analysis to investigate What Twitter says about SRL? This work uses three main analysis methods, descriptive, topic modeling, and geocoding analysis. The searched and collected dataset consists of a large volume of relevant SRL tweets equal to 54,070 tweets between 2011 and 2021. The descriptive analysis uncovers a growing discussion on SRL on Twitter from 2011 till 2018 and then markedly decreased till the collection day. For topic modeling, the text mining technique of Latent Dirichlet allocation (LDA) was applied and revealed insights on computationally processed topics. Finally, the geocoding analysis uncovers a diverse community from all over the world, yet a higher density representation of users from the Global North was identified. Further implications are discussed in the paper. [ABSTRACT FROM AUTHOR]

Grounded in the self-determination theory and the metacognitive and affective model of self-regulated learning, this study investigated the longitudinal relationship of self-determined motivation as the antecedent and academic performance as the consequence of metacognitive knowledge (MK) in mathematics learning. Two waves of data were collected from senior high school students (N = 327) in the second semester in Grades 10 and 11. A longitudinal mediation model was analyzed using structural equation modeling. Results revealed that autonomous motivation was positively related to MK of competence-enhancing strategies and negatively related to MK of avoidance strategies. Furthermore, mathematics performance was positively predicted by MK of cognitive/metacognitive strategies and negatively predicted by MK of avoidance strategies. This study expands the understanding of MK and elaborates on the dynamics between MK, self-determined motivation, and mathematics performance. Especially, this study differentiates the MK of adaptive and maladaptive strategies and examines their motivational antecedents and academic effects. Our findings also suggest that autonomous motivation has longitudinal benefits on MK. [ABSTRACT FROM AUTHOR]

Social network services such as Twitter are important venues that can be used as rich data sources to mine public opinions about various topics. In this study, we used Twitter to collect data on one of the most growing theories in education, namely Self-Regulated Learning (SRL) and carry out further analysis to investigate What Twitter says about SRL? This work uses three main analysis methods, descriptive, topic modeling, and geocoding analysis. The searched and collected dataset consists of a large volume of relevant SRL tweets equal to 54,070 tweets between 2011 and 2021. The descriptive analysis uncovers a growing discussion on SRL on Twitter from 2011 till 2018 and then markedly decreased till the collection day. For topic modeling, the text mining technique of Latent Dirichlet allocation (LDA) was applied and revealed insights on computationally processed topics. Finally, the geocoding analysis uncovers a diverse community from all over the world, yet a higher density representation of users from the Global North was identified. Further implications are discussed in the paper.

Grounded in the self-determination theory and the metacognitive and affective model of self-regulated learning, this study investigated the longitudinal relationship of self-determined motivation as the antecedent and academic performance as the consequence of metacognitive knowledge (MK) in mathematics learning. Two waves of data were collected from senior high school students (N = 327) in the second semester in Grades 10 and 11. A longitudinal mediation model was analyzed using structural equation modeling. Results revealed that autonomous motivation was positively related to MK of competence-enhancing strategies and negatively related to MK of avoidance strategies. Furthermore, mathematics performance was positively predicted by MK of cognitive/metacognitive strategies and negatively predicted by MK of avoidance strategies. This study expands the understanding of MK and elaborates on the dynamics between MK, self-determined motivation, and mathematics performance. Especially, this study differentiates the MK of adaptive and maladaptive strategies and examines their motivational antecedents and academic effects. Our findings also suggest that autonomous motivation has longitudinal benefits on MK.

This study developed a personalized mobile-assisted system with a self-regulated learning (SRL) mechanism to facilitate English-as-a-foreign-language (EFL) students' learning of grammar. A quasi-experimental design, involving an experimental group (n = 278) and a control group (n = 320), was adopted to examine its effectiveness on students' grammar learning. The experimental group, who had full access to the functions of the system (i.e., recommendations, feedback and an e-portfolio package), used the system to learn grammar, complete grammar exercise, and engage in for a semester, while the control group only use the system to submit weekly assignments. The results suggest that the experimental group obtained significantly higher scores in English grammar tests than the control group and the system benefited both genders with no significant differences. The findings provide empirical evidence in support of the effectiveness of this system in improving students' grammar test scores, indicating its value as a supplementary tool to conventional classroom teaching of English grammar via supporting learners' SRL development in a m-learning context. The pedagogical implications for applying this system in classrooms and beyond were discussed. [ABSTRACT FROM AUTHOR]

This study intended to fill the gap of undergraduates' academic motivation in Malaysia and Indonesia where, to date, little study has been done. It investigated and compared undergraduates' academic motivation levels in English online classes in two universities in both countries. Online questionnaires on students' self-regulated learning (SRL) and self-efficacy towards online learning adapted from Motivated Strategies for Learning Questionnaire (MSLQ) were distributed to 206 undergraduates from University A in Malaysia and 174 undergraduates from University B in Indonesia. Switching from physical traditional to online classes is the new norm that could be challenging and demotivating, but the results showed that the students from both universities achieved mostly high mean scores of the SRL and self-efficacy items. This indicated that their academic motivation levels were high, they were in control over their learning process, and have positive perceptions towards online classes. This uniformity also implied that although English is a second language in Malaysia, and a foreign language in Indonesia, the undergraduates were not affected by their linguistics, and institutional contexts. This study has contributed towards the extension of the current knowledge involving undergraduates' academic motivation towards learning English online and suggested that teachers could help to strategise students' SRL and selfefficacy to increase their English language performances, particularly in the pandemic era. Further research could explore the effects of academic motivation on learning outcomes or language performance as this could assist teachers to improve learners' English proficiency in online classes. [ABSTRACT FROM AUTHOR]

This study developed a personalized mobile-assisted system with a self-regulated learning (SRL) mechanism to facilitate English-as-a-foreign-language (EFL) students’ learning of grammar. A quasi-experimental design, involving an experimental group (n = 278) and a control group (n = 320), was adopted to examine its effectiveness on students’ grammar learning. The experimental group, who had full access to the functions of the system (i.e., recommendations, feedback and an e-portfolio package), used the system to learn grammar, complete grammar exercise, and engage in for a semester, while the control group only use the system to submit weekly assignments. The results suggest that the experimental group obtained significantly higher scores in English grammar tests than the control group and the system benefited both genders with no significant differences. The findings provide empirical evidence in support of the effectiveness of this system in improving students’ grammar test scores, indicating its value as a supplementary tool to conventional classroom teaching of English grammar via supporting learners’ SRL development in a m-learning context. The pedagogical implications for applying this system in classrooms and beyond were discussed.