Self-regulated Learning Processes Research Articles

Technology for organizing self-regulated learning at the stage of early professionalization of high school students in psychological and pedagogical classes

Importance. In the modern world, the role of the teacher has changed, and now students – future teachers are faced with the task of not only teaching, but also being prepared for constant self-development, professional growth and continuous learning. Modern regulatory documents of the teacher education system define competence that promotes self-education as necessary for mastery by a future teacher. Developing the ability for self-regulation in students in the pedagogical education system has great potential for successful professional development. Therefore, it is important to organize an effective process of self-regulated learning in a modern school at the stage of early professionalization in psychological and pedagogical classes. The purpose of the study is to develop and substantiate a technology for organizing self-regulated learning that promotes successful readiness for personal and professional development of high school students – students of psychological and pedagogical classes.Research Methods. Analysis of data from theoretical and empirical research in the field of self-regulated learning, also used: analysis, synthesis, generalization, comparison and interpretation, survey.Results and Discussion. Self-regulated learning is a process in which students actively participate in their own learning activities. High school students involved in self-regulated learning show higher educational results, quickly master course materials and more often achieve their personal goals. In the context of the cognitive-technological approach to learning, an innovative technology of self-regulated learning at the stage of early professionalization of high school students in specialized psychological and pedagogical classes is scientifically substantiated, including an activity algorithm: self-diagnosis – goal setting – self-motivation – planning – implementation of personal strategy – self-reflection; as well as diagnostic and autodidactic methods. A diagnostic technique has been developed to identify the level of students’ readiness for self-regulated learning.Conclusion. Considering that self-regulated learning is a complex process that requires many years of practice, training and experience, its effective use in the format of technology for organizing self-regulated learning, especially at the stage of early professionalization in psychological and pedagogical classes. The effect is enhanced when using a cognitive-technological approach, an algorithm of stages and a set of auto-didactics methods. The designed technology is a valuable innovative tool for increasing the efficiency of psychological and pedagogical classes, as well as for research and practice in the field of teacher education.

Developing and evaluating a mobile app with a self-regulation scheme to facilitate primary students’ self-regulated vocabulary learning

This article reports on the development of Vocab+, a mobile app embedded with a self-regulation scheme that supports primary students’ whole process of self-regulated vocabulary learning (SRVL) across in-class and real-life contexts, and evaluates its impact on primary students’ perceived SRVL skills and vocabulary learning outcomes. The study lasted four months. A total of 129 Grade 4 students from three classes in a primary school in Mainland China were involved. The three classes were randomly assigned to three groups. In after-class learning contexts, Group 1 (44 students) used the Vocab + app with the self-regulation scheme, Group 2 (43 students) used the app without the self-regulation scheme, and Group 3 (42 students) did not use the Vocab + app. Data collection involved pre-and post-vocabulary tests, pre-and post-questionnaires and three focus group interviews (each involving five students) about students’ experience of using the Vocab + app for vocabulary learning. Both quantitative and qualitative data analyses were performed. The findings indicate that the learners using the Vocab + app with the self-regulation scheme exhibited significantly better SRVL skills and vocabulary learning outcomes than those using the Vocab + app without the self-regulation scheme and those not using the app. The implications of these findings are explored.

A Study on Self-Regulatory Processes in EFL Academic Writing

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.

Mapping the self in self‐regulation using complex dynamic systems approach

Complex dynamic systems offer a rich platform for understanding the individual or the person‐specific mechanisms. Yet, in learning analytics research and education at large, a complex dynamic system has rarely been framed, developed, or used to understand the individual student where the learning process takes place. Individual (or person‐specific) methods can accurately and precisely model the individual person, create person‐specific models, and devise unique parameters for each individual. Our study used the latest advances in complex systems dynamics to study the differences between group‐based and individual self‐regulated learning (SRL) dynamics. The findings show that SRL is a complex, dynamic system where different sub‐processes influence each other resulting in the emergence of non‐trivial patterns that vary across individuals and time scales, and as such far from the uniform picture commonly theorized. We found that the average SRL process does not reflect the individual SRL processes of different people. Therefore, interventions derived from the group‐based SRL insights are unlikely to be effective in personalization. We posit that, if personalized interventions are needed, modelling the person with person‐specific methods should be the guiding principle. Our study offered a reliable solution to model the person‐specific self‐regulation processes which can serve as a ground for understanding and improving individual learning and open the door for precision education. Practitioner notesWhat is already known about this topic Self‐regulation is a catalyst for effective learning and achievement. Our understanding of SRL personalization comes from insights based on aggregate group‐based data. What this paper adds Every student has their own unique SRL process that varies from the average in non‐trivial ways. We offer a credible method for mapping the individualized SRL process. SRL dynamics vary across time scales. That is, the trait dynamics are different from the state dynamics, and they should be supported differently. Implications for practice and/or policy Personalization can best be achieved if based on unique person‐specific idiographic methods. Supporting learning and SRL in particular can be more efficient when we understand the differences across time scales and persons and apply insights accordingly. The general SRL average should not be expected to work for everyone.

Entwicklung und Validierung eines Instruments zur Erfassung selbstregulierten Lernens in Lernprodukten

The analysis of students’ learning products enables a behavioral diagnosis of cognitive learning strategies and provides new information for the evaluation of learning activities. The current study aims to analyze whether organization and elaboration strategies can be measured reliably in learning products and can be validated by learning success. With a newly developed coding scheme 229 lecture summaries of 24 student teachers were examined by different high-inferent categories, which enable an efficient evaluation of the learning products. For deeper insights, 94 lecture summaries of 10 students with either high or low learning success were analytically rated by means of low-inferent categories. Overall results show an interrater reliability that is substantial for high-inferent categories and very good for low-inferent categories. Significant correlations between the usage of learning strategies for the learning products and learning success (exam grades) could be found. Students with high learning success used learning strategies of nearly all categories more frequently as those with low learning success. Limitations and potentials of the approach for diagnosing and evaluating self-regulated learning processes are discussed.

Working with an instructional video on mathematical modeling: upper-secondary students’ perceived advantages and challenges

AbstractMany instructional videos in mathematics education target knowledge of procedures and algorithms. To design instructional videos that support students in a non-algorithmic domain, such as mathematical modeling, we developed a framework based on research on heuristic worked examples and instructional videos. Because students’ perceptions play an important role in whether they will engage with a learning resource, our research questions focus on the advantages and challenges students perceive when they work with an instructional video on mathematical modeling and solve a subsequent related modeling problem. Using a video based on the developed framework, we conducted an interview study with 14 pairs of upper-secondary students. The results of the qualitative text analysis showed that the perceived advantages and challenges were related to certain design features and to the processes of self-regulated learning with the video. The students experienced challenges regarding the video’s duration, the transfer to a subsequent related modeling problem, the absence of a teacher, and self-discipline. Hence, further learner support is necessary to guide the transition from working with a video to autonomous modeling, such as combining the video with strategic instruments and teacher support. In addition, interactive video features may be essential, as the students enjoyed how those features involved them in the process of watching the video. Overall, the results indicate that instructional videos are promising for providing heuristic worked examples, offering an innovative approach for teaching and learning mathematical modeling.

Attitudes in music practice: a survey exploring the self-regulated learning processes of advanced Brazilian and Portuguese musicians.

This study aimed to investigate the Self-Regulated Learning behaviors of advanced Brazilian and Portuguese musicians and how these processes vary in terms of gender, nationality, musical instrument, quantity of practice, expertise, and professional experience. 300 participants fully completed the 22-item questionnaire "Attitudes in music practice". The sample comprised of 54.3% males, 44.0% females, and 1% non-binary; 0.7% did not respond. 68.0% (n = 204) were Brazilian, and 32.0% (n = 96) were Portuguese. The mean age was 32.70 years old (SD = 11.261), the mode was 22 years old, with a range of 18 to 66 years. Data analysis procedure included exploratory factor analysis, internal consistency, independent sample t test, analysis of variance (ANOVA), and chi-square tests. Exploratory Factor Analysis generated three factors: Practice Organization, Personal Resources, and External Resources. The results report there are no differences in SRL scores in terms of gender, nationality, and musical instrument. However, One-way ANOVA test results convey differences in SRL scores and the quantity of practice and expertise with those musicians who reported practicing for longer periods scoring more highly than participants who declared spending less time on daily practice. The results for the expertise variables suggest that more experienced and older musicians scored higher in Personal Resources and lower in External Resources indicating that, as musicians gain in experience, their metacognitive processes become more evident than the social factors of their performance.

Self-regulated learning microanalysis feedback for developing clinical skills: A pilot study

Introduction The development of clinical skills requires the appropriate use of self-regulated learning (SRL). Students’ use of key SRL processes as they perform a clinical skill can be identified by SRL microanalysis and used to provide feedback. SRL-microanalysis feedback only on students’ key SRL processes has not been previously researched for developing clinical skills. The aim of this study was to investigate whether SRL-microanalysis feedback only on students’ key SRL processes can improve both their use of SRL and their clinical skill performance. Methods Twenty-three final year medical students with no experience in the clinical skill required for mechanical ventilation participated in this study. Key SRL processes and clinical skill performance were measured before and after SRL microanalysis feedback. Results Overall, we found an improvement in the key SRL processes of planning and monitoring of performance, with a significant difference in monitoring. We also found an increase in students’ clinical skill performance. Discussion This study, which is the first in clinical skills, demonstrated that SRL microanalysis feedback only on key SRL processes can improve both students’ SRL and their clinical skill performance. studies are recommended with a great number of students and across a variety of clinical skills.

Artificial Intelligence Supporting Independent Student Learning: An Evaluative Case Study of ChatGPT and Learning to Code

Artificial intelligence (AI) tools like ChatGPT demonstrate the potential to support personalized and adaptive learning experiences. This study explores how ChatGPT can facilitate self-regulated learning processes and learning computer programming. An evaluative case study design guided the investigation of ChatGPT’s capabilities to aid independent learning. Prompts mapped to self-regulated learning processes elicited ChatGPT’s support across learning tools: instructional materials, content tools, assessments, and planning. Overall, ChatGPT provided comprehensive, tailored guidance on programming concepts and practices. It consolidated multimodal information sources into integrated explanations with examples. ChatGPT also effectively assisted planning by generating detailed schedules. However, its interactivity and assessment functionality demonstrated shortcomings. ChatGPT’s effectiveness relies on learners’ metacognitive skills to seek help and assess its limitations. The implications include ChatGPT’s potential to provide Bloom’s two-sigma tutoring benefit at scale.

Self-regulation in online string instrument lessons: Motivation, social interaction and learning environment

This article investigates selected processes of self-regulated learning (SRL) in online string instrument lessons. We explore: (i) the factors that motivate teachers and students to commence and maintain online teaching and learning, (ii) the synchronous and asynchronous social interactions that occur between teachers, students and peers and (iii) the structuring of the online/physical learning environment. The participants were five international string teachers and six students, voluntarily teaching and learning online in a non-formal educational context. Data sources include lesson observations, semi-structured interviews and questionnaires. A theoretical’ thematic analysis method was used to analyse the data. The findings indicate that the possibility of online lessons overcoming geographical barriers led to the involvement of teachers and students, and persistence came with the realisation of student performance progress. Teachers attempted to overcome the impracticability of technique-related physical manipulation by stimulating students’ mental imagery. They also reported the importance of exploring interactions through social media platforms to encourage students to seek help. To account for lessons taking place at students’ homes, teachers reinforced the importance of providing instructions to promote environmental structuring. Finally, despite the physical distance, teachers affirmed that they established bonds of affection with students.

Towards prescriptive analytics of self‐regulated learning strategies: A reinforcement learning approach

AbstractSelf‐regulated learning (SRL) is an essential skill to achieve one's learning goals. This is particularly true for online learning environments (OLEs) where the support system is often limited compared to a traditional classroom setting. Likewise, existing research has found that learners often struggle to adapt their behaviour to the self‐regulatory demands of OLEs. Even so, existing SRL analysis tools have limited utility for real‐time or individualised support of a learner's SRL strategy during a study session. Accordingly, we explore a reinforcement learning based approach to learning optimal SRL strategies for a specific learning task. Specifically, we utilise the sequences of SRL processes acted by 44 participants, and their assessment scores for a prescribed learning task, in a purpose‐built OLE to develop a long short‐term memory (LSTM) network based reward function. This is used to train a reinforcement learning agent to find the optimal sequence of SRL processes for the learning task. Our findings indicate that the developed agents were able to effectively select SRL processes so as to maximise a prescribed learning goal as measured by predicted assessment score and predicted knowledge gains. The contributions of this work will facilitate the development of a tool which can detect sub‐optimal SRL strategy in real‐time and enable individualised SRL focused scaffolding. Practitioner notesWhat is already known about this topic Learners often fail to adequately adapt their behavior to the self‐regulatory demands of e‐Learning environments. In order to promote effective Self‐regulated learning (SRL) capabilities, researchers and educators need tools that are able to analyze and diagnose a learner's SRL strategy use. Current methods for SRL analysis are more often descriptive as opposed to prescriptive and have limited utility for real‐time analysis or support of a learner's SRL behavior. What this paper adds This paper proposes the use of Reinforcement Learning for prescriptive analytics of SRL. We train a Reinforcement Learning agent on sequences of SRL processes acted by learners in order to learn the optimal SRL strategy for a given learning task. Implications for practice and/or policy Our work will facilitate the development of a tool which can detect sub‐optimal SRL strategy in real‐time and enable individualized SRL focused scaffolding. The implications of our work can aid in course design by predicting the self‐regulatory load imposed by a given task. The ability to model SRL strategies using Reinforcement Learning can be extended to simulate or test SRL theories.

Scaffolding Self-Regulated Learning in Operative Dentistry Through Self-Assessment Training.

This study aimed to investigate how effective self-assessment training is in improving the self-regulated learning (SRL) ability of operative dentistry students. The secondary aim was to explore students' attitudes towards self-assessment in clinical settings. Self-assessment has been the focus of dental education research for decades and has been claimed to be cornerstone in the SRL process. This is quasi-experimental study conducted at Damascus University Faculty of Dental Medicine, Syria. A modified direct observation of procedural skills (DOPS) assessment protocol with a self-assessment component was applied to a convenience sample of students across five clinical encounters in 2022. Data were collected during clinical training on the DOPS form and at the end of the experiment using a structured questionnaire with a single open-ended question. The qualitative part of the study followed a deductive theory-informed content analysis approach, relying on Zimmerman SRL theory. A total number of 32 students participated in the study, eight of whom were male. During the experiment assessment, participants showed overwhelming positive attitudes towards the utility of self-assessment (m ≥ 3.5; max:4) and the overall assessment method (3.3 ≥ m ≥ 3.5; max:4). Cronbach's alpha for the post-experiment questionnaire was 0.888. A total of 84.4% of the participants strongly agreed that self-assessment is useful in clinical training. Data collected (qualitative and quantitative) from participants revealed the positive effects of self-assessment on all three phases of SRL, especially the reflection phase. Self-assessment practice and training showed positive results in terms of improving SRL and performance in a clinical context; SRL appeared to be affected by self-assessment in all phases (forethought, performance, and reflection). Participants' perceptions of self-assessment were generally very positive. These findings imply the potential benefits of applying self-assessment training interventions to foster the SRL ability of learners within the clinical context.

Unveiling learning regulations through reflective notes

While self-regulated learning (SRL) has been studied in various disciplines, insufficient attentionhas been paid to how formative assessment/assessment for learning (AfL) promotes students’ SRL in learning English as foreign language (EFL) context. The present study attempted to address the gap. Forty four non-English majors in the second year of an undergraduate program at a Chinese university participated in the research. They completed 5 writing tasks, performed peer assessment, and wrote reflections to record their perceptions of the experience. Scoring rubrics was developed based on China’s Standards of English Language Abilities (CSE) for the participants to use in peer assessment and complete a peer assessment report for essay revision. Analysis of the reflections suggests that CSE rubrics referenced peer assessment involved extensive SRL processes of planning, monitoring, regulating, reflecting, and resource management, which were closely related to three contextual artifacts: rubric, peer assessment report, and essay script. These are important factors in support of the participants’ SRL engagement from a social cognitive perspective. Implications are discussed with reference to language teaching and learning with a view to developing EFL learners’ SRL capacity.

Examining change in students’ self-regulated learning patterns after a formative assessment using process mining techniques

The growing popularity of e-learning platforms, such as learning management systems, has foregrounded the role of self-regulated learning (SRL) in student success. In many e-learning environments, students typically complete learning assignments outside of school hours with little or no instructor support, which requires students to be highly self-regulated. The current study used trace data from a Moodle platform to examine both the temporal pattern of students' SRL behaviors and changes in high- and low-performing students' SRL behaviors following a formative in-course exam. This study employed repeated-measures ANOVA, multivariate ANOVA, Fuzzy miner, and pMineR on 122,167 event logs from 527 undergraduate students. Findings revealed that students engaged in a loosely sequenced recursive SRL cycle. Following the formative assessment, each group made different adjustments to their SRL processes. High-performing students exhibited more SRL behaviors and developed more structured and interconnected SRL patterns. Low-performing students displayed a smaller increase in SRL behaviors while maintaining their established SRL patterns. Findings from this study could provide a more in-depth theoretical understanding of the nature of SRL cycles. Furthermore, students’ adjustment of SRL patterns in response to assessment may be informative for practitioners to assist students in enhancing their SRL through formative feedback.

Role of Theory in Analysing the dynamic of Self-regulated Learning process based on students’ event logs data: A scoping review

Students' capability to metacognitively regulate themselves—cognitively or behaviourally—in their learning plays a pivotal role in determining their academic performance. The dynamic aspect of Self-Regulated Learning (SRL) will be challenging to capture if it relies on perceptual data obtained from students through questionnaires and interviews and only at specific points in time. One potential alternative is to use an approach that captures student activity data in real-time throughout the learning period. Given the context-sensitivity involved in measuring SRL via event data, a solid theoretical foundation is essential in analysing patterns of SRL behaviour using event log data. This scoping review paper aims to identify and map how the empirical studies in this area consider SRL theory or models, not only when interpreting analytical results but also when designing instruction and interpreting SRL indicators from raw data. A thorough literature search was performed on various online databases, including Scopus, IEEExplorer, ProQuest, and Web of Science, to identify relevant studies. Following the PRISMA scoping review (PRISMA-ScR) as a protocol for the review, 39 studies published between 2012 and 2023 were included. This study found limited studies incorporating SRL theory in every analysis stage, from designing instruction to preprocessing event data and interpreting analytical models. This study also highlighted the importance of including contextual and theoretical factors when assessing self-regulatory behavioural patterns.

How to design and evaluate personalized scaffolds for self-regulated learning

Self-regulation is an essential skill for lifelong learning. Research has shown that self-regulated learning (SRL) leads to greater academic achievement and sustainable education, but students often struggle with SRL. Scaffolds are widely reported as an effective and efficient support method for SRL. To further improve digital scaffolds’ effectiveness, real-time detection of learning behavior can be used to personalize scaffolds. Therefore, the present study aimed to inform the field of scaffolding SRL by reporting on the design and evaluation of digital scaffolds. We present decisions made during the design process of personalized scaffolds to inform future scaffold designs. We evaluated how scaffolds were personalized based on real-time detection SRL, how university students respond to the scaffolds (i.e., compliance), and how this response is related to learning outcomes (i.e., quality of an essay). The research design was a pre-posttest with three conditions (no, generalized (same for all), or personalized scaffolds). A 45-minute reading and writing task was used, during which SRL processes were recorded in real-time. Findings revealed that different real-time SRL processes could be used to personalize scaffolds, meaning that we were able to personalize the content of scaffold based on students’ actual learning behavior. In addition, students in the personalized condition complied more with the scaffolds than students in the other conditions. This compliance with the scaffolds was generally associated with better learning outcomes. To conclude, our approach showed how design decisions could be evaluated and provided insight into the personalization of scaffolds.

Self-Regulated Learning Diary Interventions and the Implications for Health Professions Education

Background. There is increasing interest in the application of self-regulated learning (SRL) to improve academic and clinical performance in health professions education. SRL-learning diary (SRL-LD) interventions have become popular in non-health professions contexts to develop students’ SRL and academic performance. The aim of this systematic review was to identify how SRL-LD interventions have been used in health and non-health professions education, with the intention to provide insights into their use and to inform future implementation and research in health professions education. Methods. Electronic search in ERIC, ProQuest, PubMed, Scopus, Embase, and Web of Science was conducted. Two authors independently selected studies based on inclusion criteria and all selected studies were analyzed using a predetermined framework. Results. Of the identified 986 studies, 23 were selected for the review. Most studies were conducted in higher education within a domain-specific context, with only one study in health professions education. Most were justification studies. Five types of intervention were identified (Diary + SRL instruction, Diary + feedback, Diary + SRL instruction + feedback, Diary only, and SRL instruction only). Overall, the combination of a diary with explicit SRL instruction and/or feedback improved more SRL processes than diary only or SRL instruction only interventions. In studies reporting academic outcomes, there was also an improvement in 40% of studies. Conclusion. This systematic review highlights the potential usefulness of SRL-LD interventions in health professions education. Recommendations for implementation and future research are discussed.

Patronizing behavior in heterogeneous teams: A laboratory experiment

Collaboration among group members in organizations is highly prevalent and often encouraged. Yet, inefficient task assignment and patronizing may weaken the self-regulated learning process of an inexperienced group member. In a laboratory experiment, we exogenously vary the environment in which cooperative, heterogeneous groups interact. First, we introduce a time budget for task completion that is shared by both team members, and second, asymmetric information about the inexperienced group member’s scope for learning. Our results show that patronizing increases significantly with higher uncertainty and perceived time pressure, decreases team performance in the long run, and correlates with time and risk preferences.

Relations between undergraduates’ self-regulated learning skill mastery during digital training and biology performance

Undergraduate STEM lecture courses enroll hundreds who must master declarative, conceptual, and applied learning objectives. To support them, instructors have turned to active learning designs that require students to engage in self-regulated learning (SRL). Undergraduates struggle with SRL, and universities provide courses, workshops, and digital training to scaffold SRL skill development and enactment. We examined two theory-aligned designs of digital skill trainings that scaffold SRL and how students’ demonstration of metacognitive knowledge of learning skills predicted exam performance in biology courses where training took place. In Study 1, students’ (n = 49) responses to training activities were scored for quality and summed by training topic and level of understanding. Behavioral and environmental regulation knowledge predicted midterm and final exam grades; knowledge of SRL processes did not. Declarative and conceptual levels of skill-mastery predicted exam performance; application-level knowledge did not. When modeled by topic at each level of understanding, declarative knowledge of behavioral and environmental regulation and conceptual knowledge of cognitive strategies predicted final exam performance. In Study 2 (n = 62), knowledge demonstrated during a redesigned video-based multimedia version of behavioral and environmental regulation again predicted biology exam performance. Across studies, performance on training activities designed in alignment with skill-training models predicted course performances and predictions were sustained in a redesign prioritizing learning efficiency. Training learners’ SRL skills –and specifically cognitive strategies and environmental regulation– benefited their later biology course performances across studies, which demonstrate the value of providing brief, digital activities to develop learning skills. Ongoing refinement to materials designed to develop metacognitive processing and learners’ ability to apply skills in new contexts can increase benefits.

Capturing self‐regulated learning processes in virtual reality: Causal sequencing of multimodal data

AbstractThis study examines the embodied ways in which learners monitor their cognition while learning about exponential functions in an immersive virtual reality (VR) based game, Pandemic by Prisms of Reality. Traditionally, metacognitive monitoring has been assessed through behavioural traces and verbalised instances. When learning in VR, learners are fully immersed in the learning environment, actively manipulating it based on affordances designed to support learning, offering insights into the relationship between physical interaction and metacognition. The study collected multimodal data from 15 participants, including think‐aloud audio, bird's‐eye view video recordings and physiological data. Metacognitive monitoring was analysed through qualitative coding of the think‐aloud protocol, while movement was measured via optical flow analysis and cognitive load was assessed through heart rate variability analysis. The results revealed embodied metacognition by aligning the data to identify learners' physical states alongside their verbalised metacognition. The findings demonstrated a temporal interplay among cognitive load, metacognitive monitoring, and motion during VR‐based learning. Specifically, cognitive load, indicated by the low‐ and high‐frequency heart rate variability index, predicted instances of metacognitive monitoring, and monitoring predicted learners' motion while interacting with the VR environment. This study further provides future directions in understanding self‐regulated learning processes during VR learning by utilizing multimodal data to inform real‐time adaptive personalised support within these environments. Practitioner notesWhat is already known about this topic Immersive virtual reality (VR) environments have the potential to offer personalised support based on users' individual needs and characteristics. Self‐regulated learning (SRL) involves learners monitoring their progress and strategically regulating their learning when needed. Multimodal data captured during VR learning, such as birds‐eye‐view video, screen recordings, physiological changes and verbalisations, can provide insights into learners' SRL processes and support needs. What this paper adds Provides insights into the embodied aspects of learners' metacognitive monitoring during learning in an immersive VR environment. Demonstrates how SRL processes can be captured via the collection and analysis of multimodal data, including think‐aloud audio, bird's‐eye view video recordings and physiological data, to capture metacognitive monitoring and movement during VR‐based learning. Contributes to the understanding of the interplay between cognitive load, metacognitive monitoring, and motion in immersive VR learning. Implications for practice and/or policy Researchers and practitioners can use the causal relationships identified in this study to identify instances of SRL in an immersive VR setting. Educational technology developers can consider the integration of online measures, such as cognitive load and physiological arousal, into adaptive VR environments to enable real‐time personalised support for learners based on their self‐regulatory needs.