Self-regulated Learning Processes Research Articles

College online courses have strong design in scaffolding but vary widely in supporting student agency and interactivity

This study develops a rubric comprising three quality concepts critical to addressing online learning challenges: Scaffolding, which supports student self-regulated learning processes; Student Agency, which promotes student choices and voices; and Social Presence and Interpersonal Interaction, which enhances student connection with peers and instructors. We then examine the extent to which college online courses reflect the three concepts following a 3-point scoring scale (“beginning,” “developing,” or “proficient”) based on observation data collected from 100 randomly selected courses. Our results indicate that about two-thirds of the courses score at or above the developing level, demonstrating some but insufficient incorporation of design features that can enhance the three concepts. While most courses are above the developing level for “Scaffolding,” less than half and less than one-third reach the developing level for the other two concepts. We further identify variations in course design based on instructor characteristics, where female instructors, instructors with higher educational attainment, and instructors teaching fewer credit hours had higher scores.

Exploring the co‐occurrence of students' learning behaviours and reasoning processes in an intelligent tutoring system: An epistemic network analysis

AbstractBackgroundMedical students use a variety of self‐regulated learning (SRL) strategies in different medical reasoning (MR) processes to solve patient cases of varying complexity. However, the interplay between SRL and MR processes is still unclear.ObjectivesThis study investigates how self‐regulated learning (SRL) and medical reasoning (MR) occurred concurrently in medical students while completing a diagnostic task in an intelligent tutoring system. This study aims to provide new insights into performance differences between high‐ and low‐achieving students in tasks of varying complexity.MethodsThirty‐one medical students (67.6% female) from a large North American university were tasked with solving two virtual patient cases in an intelligent tutoring system, BioWorld. BioWorld was designed for medical students to practice clinical reasoning skills deliberately. We collected students' think‐aloud protocols, based on which we coded their use of SRL behaviours and medical reasoning activities. We analysed the co‐occurrences of SRL behaviours and medical reasoning activities using the epistemic network analysis (ENA) method.ResultsThe SRL behaviour self‐reflection and MR activity lines of reasoning co‐occurred more frequently in a difficult task than in an easy task. In both tasks, high performers demonstrated more co‐occurrences of self‐reflection and lines of reasoning than low performers. Moreover, the MR activity conceptual operations co‐occurred more frequently with the SRL activities of monitoring and evaluation among high performers compared to low performers in an easy task.ImplicationsThe co‐occurrences of SRL behaviours and MR processes account for students' performance differences. The design of computer‐based learning environments for clinical reasoning should promote the acquisition of both SRL and medical reasoning abilities. Moreover, medical educators should consider task complexity when scaffolding.

Self-regulated learning processes across different physiotherapy clinical procedural skills and time intervals: A SRL microanalysis study

Purpose of the study The performance of a clinical procedural skill by an individual student is associated with their use of Self-Regulated Learning (SRL) processes. However, previous research has not identified if an individual student has a similarity in their use of SRL processes across different clinical procedural skill tasks and at a time interval. The aim of this pilot study was to explore the similarity in the use of SRL processes by individual students across different clinical procedural skill tasks and at a time interval. Methods SRL-microanalysis was used to collect within-subject data on undergraduate physiotherapy students’ use of the two key SRL processes (planning and monitoring) during their performance of different goniometry clinical procedural skills tasks and also at a fourth month interval. Results An individual student’s use of key SRL processes across different clinical procedural skill tasks and at a time interval was similar. Also, this similarity was identified for students with initial successful and unsuccessful performances. Conclusion Our findings have implications for the future wider practical implementation of SRL microanalysis to inform personalised SRL feedback for developing the clinical procedural skills of individual students. Further research with a greater number of students and across a wider range of clinical procedural skills will be required to confirm our findings, and also its effectiveness on feedback and future performance.

Cyclical phases and processes of self-regulated learning

"Cyclical phases and processes of self-regulated learning." Medical Teacher, ahead-of-print(ahead-of-print), pp. 1–2

Towards a fuller picture: Triangulation and integration of the measurement of self‐regulated learning based on trace and think aloud data

AbstractBackgroundMany learners struggle to productively self‐regulate their learning. To support the learners' self‐regulated learning (SRL) and boost their achievement, it is essential to understand the cognitive and metacognitive processes that underlie SRL. To measure these processes, contemporary SRL researchers have largely utilized think aloud or trace data, however, not without challenges.ObjectivesIn this paper, we present the findings of a study that investigated how concurrent analysis and integration of think aloud and trace data could advance the measurement of SRL and assist in better understanding the mechanisms of SRL processes, especially those details that remain obscured by observing each data channel individually.MethodsWe concurrently collected think aloud and trace data generated by 44 university students in a laboratory setting and analysed those data relative to the same timeline.ResultsWe found that the two data channels could be interchangeably used to measure SRL processes for only 17.18% of all the time segments identified in a learning task. Moreover, SRL processes for around 45% of all the time segments could be detected via either trace data or think aloud data. For another 27.17% of all the time segments, different SRL processes were detected in both data channels.ConclusionsOur results largely suggest that the two data collection methods can be used to complement each other in measuring SRL. In particular, we found that think aloud and trace data could provide different perspectives on SRL. The integration of the two methods further allowed us to reveal a more complex and more comprehensive temporal associations among SRL processes compared to using a single data collection method. In future research, the integrated measurement of SRL can be used to improve the detection of SRL processes and provide a fuller picture of SRL.

Ticket to perform: an explorative study of trainees’ engagement in and transfer of surgical training

BackgroundResearch suggests that simulation-based surgical skills training translates into improved operating room performance. Previous studies have predominantly focused on training methods and design and subsequent assessable performances and outcomes in the operating room, which only covers some aspects of training engagement and transfer of training. The purpose of this qualitative study was to contribute to the existing body of literature by exploring characteristics of first-year trainees’ engagement in and perceptions of transfer of surgical skills training.MethodsWe conducted an explorative study based on individual interviews with first-year trainees in General Surgery, Urology, and Gynaecology and Obstetrics who participated in a laparoscopic skills training program. Informants were interviewed during and two months after the training program. A thematic cross-case analysis was conducted using systematic text condensation.ResultsWe interviewed 12 informants, which produced 24 transcripts for analysis. We identified four main themes: (1) sportification of training, (2) modes of orientation, (3) transferrable skills, and (4) transfer opportunities. Informants described their surgical training using sports analogies of competition, timing, and step-by-step approaches. Visual orientations, kinaesthetic experiences, and elicited dialogues characterised training processes and engagement. These characteristics were identified in both the simulated and the clinical environment. Experiences of specific skills transfer included ambidexterity, coordination, instrument handling, and visuospatial ability. General transfer experiences were salient in informants’ altered training approaches. Informants considered the simulation-based training an entry ticket to perform in the operating room and mentioned supervisor-trainee relationships and opportunities in the workplace as critical conditions of transfer.ConclusionsOur findings elucidate characteristics of surgical training engagement that can be interpreted as self-regulated learning processes that transcend surgical training environments. Despite appreciating the immediate skills improvements resulting from training, trainees’ narratives reflected a struggle to transfer their training to the clinical setting. Tensions existed between perceptions of transferable skills and experiences of transfer within the clinical work environments. These results resonate with research emphasising the importance of the work environment in the transfer process. Our findings provide insights that may inform the development of training programs that support self-regulated learning and transfer of training from the simulated to the clinical environment.

Reinforcement learning for automatic detection of effective strategies for self-regulated learning

Self-regulated learning (SRL) is an essential skill for achieving one's learning goals, particularly in Digital Learning Environments (DLEs) where system support is often limited compared to traditional classroom settings. However, research has found that learners often struggle to adapt their behaviour to the self-regulatory demands of DLEs. Furthermore, existing SRL analysis tools have limited utility for real-time or individualized prescriptive support of a learner's SRL strategy during a study session.In response to these challenges, we propose a novel approach using reinforcement learning as a framework to optimize the sequence of SRL processes for a learning task. This framework allows us to model and optimize the SRL strategy as a sequential decision-making problem, where each decision corresponds to an SRL process. The goal is to find an optimal sequence of decisions that maximizes performance in learning outcomes such as assessment score or learning gains.We compare the performance of our reinforcement learning framework with other sequential machine learning tools, such as Long Short-Term Memory (LSTM) neural networks and Genetic Algorithms (GA). The results of our study show that our reinforcement learning model outperforms GA and LSTM models in optimizing SRL strategy.The contributions of this work can facilitate the development of a tool which can detect sub-optimal SRL strategy in real-time and enable individualized SRL focused scaffolding.

Self-Regulated Learning Strategies on Academic Writing: Differences Between Genders

Six categories—motivation, method, timing, performance, physical environment, and social environment—are used to classify self-regulated learning (SRL) processes in academic writing. Due to the more difficult academic papers, they must write in English, university students may adopt SRL methods when generating academic writing. Students who are male or female may have various preferences when it comes to using SRL techniques in academic writing. The purpose of this study is to examine the aspect of SRL that English Language Education Department (ELED) students use the most frequently and to determine whether there is a statistically significant difference in the attitudes of male and female ELED students toward the usage of SRL tactics in academic writing. The research design for this study is a survey, and it uses a quantitative methodology. 112 ELED students from the 2019 batch participated in this study and answered the “The six dimensions of SRL in academic writing” questionnaire, which was adapted from Abadikhah, Aliyan, and Talebi (2018). The results showed that students implement all six aspects equally, with the social environment dimension having the highest mean (M=3.76, SD=.60) and the time dimension having the lowest mean (M=3.09, SD=.65). The t-test result is.439. This means that the significance level is less than 0.05 (2-tailed). Therefore, it may be inferred that attitudes concerning the use of SRL methods in academic writing are similar for both male and female students.

Goal-setting in support of learning during search: An exploration of learning outcomes and searcher perceptions

We present a crowdsourced study (N=120) that investigated the role of goal-setting on learning during search. To study the role of goal-setting, we developed a tool called the Subgoal Manager (SM). The SM was designed as a simple tool to help searchers deconstruct a learning-oriented search task into smaller subgoals, take notes with respect to specific subgoals, and mark subgoals as completed. During the study, participants completed one learning-oriented search task that focused on learning about the concepts of diffusion and osmosis. After the search task, participants completed a multiple-choice test that measured deep understanding of diffusion and osmosis. The study used a between-subjects design with three subgoal conditions. In the SelfSetSubgoals condition, participants had access to the SM and set their own subgoals. Participants were instructed to set high-quality subgoals that included a specific action, content, standard, and time. In the AssignedSubgoal condition, participants had access to the SM with pre-written, high-quality subgoals. Participants could take notes with respect to specific subgoals and mark subgoals as completed, but could not edit, delete, nor add new subgoals during the search session. Finally, in the NoSubgoals condition, participants were not instructed to generate subgoals and were simply provided with a text editor tool to take notes. We investigate the effects of the subgoal condition on learning outcomes and perceptions of: the task, support for specific self-regulated learning processes, the quality of subgoals pursued during the task, and engagement. Our results found that participants had the best outcomes in the SelfSetSubgoals condition. Additionally, within the SelfSetSubgoals condition, outcomes were even better when participants set high-quality subgoals.

A Narrative Review of Eye-tracking Research on Self-regulated Learning from Multimedia Learning Materials in Higher Education

This study provides a narrative review of current eye-tracking research on self-regulated learning from multimedia learning materials in higher education. The main aim of the review is to explore how eye tracking is used in self-regulated learning research when learning from multimedia materials in university students. Other specific aims were established: 1) to identify what self-regulated learning processes are explored with eye tracking while learning from multimedia materials, 2) to determine what methods are used to explore self-regulated learning processes with eye tracking, 3) to find what structures and stimuli are used in eye-tracking experiments when studying self-regulated learning processes, and 4) to investigate what eye-tracking metrics are used to study self-regulated learning processes in learning from multimedia materials. To accomplish these aims, we analyzed 11 empirical studies published between 2012 and 2021. The results show that 1) current studies focus on self-regulated learning processes, such as judgments of learning, metacognitive monitoring, meta-comprehension, and learning strategies, 2) studies are quantitative and use experimental designs, specific stimuli, and distinct structures, and 4) studies are mainly focused on the fixations, saccades, and transitions between selected areas of interest in the data analyses. The results of this narrative review can indicate new directions for future research in this field.

Measuring self-regulated learning and the role of AI: Five years of research using multimodal multichannel data

Learning sciences are embracing the significant role technologies can play to better detect, diagnose, and act upon self-regulated learning (SRL). The field of SRL is challenged with the measurement of SRL processes to advance our understanding of how multimodal data can unobtrusively capture learners' cognitive, metacognitive, affective, and motivational states over time, tasks, domains, and contexts. This paper introduces a self-regulated learning processes, multimodal data, and analysis (SMA) grid and maps joint and individual research of the authors (63 papers) over the last five years onto the grid. This shows how multimodal data streams were used to investigate SRL processes. The two-dimensional space on the SMA grid is helpful for visualizing the relations and possible combinations between the data streams and how the measurement of SRL processes. This overview serves as an analytical introduction to the current special issue “Advancing SRL Research with Artificial Intelligence (AI)” and we encourage to position new research and unexplored frontiers. We emphasize the need for intensive and strategic collaboration to accelerate progress using new interdisciplinary methods to develop accurate measurement of SRL in educational technologies.

Supporting self-regulated learning with learning analytics interventions – a systematic literature review

During the past years scholars have shown an increasing interest in supporting students' self-regulated learning (SRL). Learning analytics (LA) can be applied in various ways to identify a learner’s current state of self-regulation and support SRL processes. It is important to examine how LA has been used to identify the need for support in different phases of SRL cycle, which channels are used to mediate the intervention and how efficient and impactful the intervention is. This will help the learners to achieve the anticipated learning outcomes. The systematic literature review followed PRISMA 2020 statement to examine studies that applied LA interventions to enhance SRL. The search terms used for this research identified 753 papers in May 2021. Of these, 56 studies included the elements of LA, SRL, and intervention. The reviewed studies contained various LA interventions aimed at supporting SRL, but only 46% of them revealed a positive impact of an intervention on learning. Furthermore, only four studies reported positive effects for SRL and covered all three SRL phases (planning, performance, and reflection). Based on the findings of this literature review, the key recommendation is for all phases of SRL to be considered when planning interventions to support learning. In addition, more comparative research on this topic is needed to identify the most effective interventions and to provide further evidence on the effectiveness of interventions supporting SRL.

Progression of students' SRL processes in subsequent programming problem-solving tasks and its association with tasks outcomes

Learning programming is difficult, and many students fail or have poor outcomes. To learn to program means to master steps in the complex problem-solving activity. Previous research uncovered a rich set of domain-specific and generic cognitive and metacognitive strategies students use when they learn to program. The processes that problem-solving experts demonstrate are very similar to those studied by self-regulated learning researchers. This study proposes Self-Regulated Learning (SRL) process types derived from the SRL phases indicators developed from log data captured from students' interaction with the instructional scaffold for programming assignments in LMS. The process types were defined from theoretical and pragmatic perspectives, with the aim to indicate concrete interventions for improving problemsolving skills. We have observed and quantified students' use of the SRL processes of distinct types in the series of five problem-solving assignments. We have also observed the progression of SRL processes used by each student in the assignments. Our modelling showed that students with domain knowledge at the same level achieve higher assignment marks when they demonstrate SRL processes at the higher level; importantly, students with the lowest programming skills benefit the most.

System design for using multimodal trace data in modeling self-regulated learning

Self-regulated learning (SRL) integrates monitoring and controlling of cognitive, affective, metacognitive, and motivational processes during learning in pursuit of goals. Researchers have begun using multimodal data (e.g., concurrent verbalizations, eye movements, on-line behavioral traces, facial expressions, screen recordings of learner-system interactions, and physiological sensors) to investigate triggers and temporal dynamics of SRL and how such data relate to learning and performance. Analyzing and interpreting multimodal data about learners' SRL processes as they work in real-time is conceptually and computationally challenging for researchers. In this paper, we discuss recommendations for building a multimodal learning analytics architecture for advancing research on how researchers or instructors can standardize, process, analyze, recognize and conceptualize (SPARC) multimodal data in the service of understanding learners' real-time SRL and productively intervening learning activities with significant implications for artificial intelligence capabilities. Our overall goals are to (a) advance the science of learning by creating links between multimodal trace data and theoretical models of SRL, and (b) aid researchers or instructors in developing effective instructional interventions to assist learners in developing more productive SRL processes. As initial steps toward these goals, this paper (1) discusses theoretical, conceptual, methodological, and analytical issues researchers or instructors face when using learners' multimodal data generated from emerging technologies; (2) provide an elaboration of theoretical and empirical psychological, cognitive science, and SRL aspects related to the sketch of the visionary system called SPARC that supports analyzing and improving a learner-instructor or learner-researcher setting using multimodal data; and (3) discuss implications for building valid artificial intelligence algorithms constructed from insights gained from researchers and SRL experts, instructors, and learners SRL via multimodal trace data.

Tools Designed to Support Self-Regulated Learning in Online Learning Environments: A Systematic Review

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.

Improving the measurement of self-regulated learning using multi-channel data

In recent years, unobtrusive measures of self-regulated learning (SRL) processes based on log data recorded by digital learning environments have attracted increasing attention. However, researchers have also recognised that simple navigational log data or time spent on pages are often not fine-grained enough to study complex SRL processes. Recent advances in data-capturing technologies enabled researchers to go beyond simple navigational logs to measure SRL processes with multi-channel data. What multi-channel data can reveal about SRL processes, and to what extent can the addition of peripheral and eye-tracking data with navigational log data change and improve the measurement of SRL are key questions that require further investigation. Hence, we conducted a study and collected learning trace data generated by 25 university students in a laboratory setting, that aimed to address this problem by enhancing navigational log data with peripheral and eye-tracking data. We developed a trace-based measurement protocol of SRL, which interpreted raw trace data from multi-channel data into SRL processes. Specifically, the study compared the frequency and duration of SRL processes detected, how much duration and times of occurrences of the detected SRL processes were affected or refined. We also used a process mining technique to analyses how temporal sequencing of the detected SRL processes changed by enriching navigational log data with peripheral and eye-tracking data. The results revealed that by adding new data channels, we improved the capture of learning actions and detected SRL processes while enhancing the granularity of the measurement. In comparison to the use of navigational logs only, the completeness of temporal sequencing relationships between SRL processes with multi-channel data improved. In addition, we concluded that eye-tracking data is valuable for measuring and extracting SRL processes, and it should receive more attention in the future.

Students’‎ Readiness for Self-Regulated Smart Learning Environment

The increasing development in smart and mobile technologies supports transformation of learning environment into a smart learning environment to meet diverse learners’ needs. Learning in an online environment requires motivation and skills to succeed. Self-regulated learning has been identified as one of the strategies for supporting students in an online learning environment. However, despite these innovations, there is a scarcity of well exploratory works to understand if students have skills, experiences, and technology resources for implementing a self-regulated smart learning environment. This study attempts to fill the gaps by investigating these experiences and technology resources. The study used mixed-method to investigate the readiness of 157 undergraduate students. The quantitative data used an online self-regulated learning questionnaire (OSLQ), and the qualitative data used focus group discussions. The quantitative data were analyzed using descriptive statistics and correlations, and the qualitative data used a thematic method to understand students’ experiences. The investigations show that students understood the self-regulated learning process and its’ role in their academic success. Moreover, they have access to mobile internet services and smart devices, mostly an android operating system. More so, goal setting, time management, and self-evaluation are among the top-level skills readiness, and there is a relationship between previous online learning experiences and these skills. Future research could investigate facilitators’ readiness to develop a self-regulated smart learning environment for engaging online learning experiences and skills development.

Preservice Science Teachers’ Perspectives on and Practices Related to Self-Regulated Learning after a Brief Learning Opportunity

Teacher education programs are a critical site for preparing teachers’ self-regulated learning (SRL) knowledge and capacity to foster students’ SRL skills. The present study describes preservice science teachers’ (PSTs) perspectives and practices regarding SRL after a brief learning opportunity. The participants were 12 PSTs in a certification program for teaching secondary science. The data came from course assignments, lesson plans, and semi-structured interviews. The findings showed the PSTs appreciated the role of SRL and tried to integrate SRL processes into their science lessons. However, they needed further support to systematically implement SRL processes in classrooms. Findings from this study are relevant for science teacher educators who are interested in improving science teaching because the link between SRL and science teaching is discussed. They may also support teacher educators in making more informed decisions about course design and instruction regarding SRL. Finally, since suggestions for future studies are discussed, this research is relevant for science education researchers who study teachers’ perspectives on and practices related to SRL.

Perceived Classroom Assessment Environment and Autonomous Motivation as Predictors of Students’ Achievement Emotions in Relation to Learning for Baccalaureate Exam

"Achievement emotions constitute an important individual variable in the complex process of self-regulated learning, through its effects not only on student's well-being, but also on academic performance. Exploring the individual and contextual correlates of this type of emotions experienced by students in the educational environment is important for both improving the learning climate and developing an optimal self-regulation. In this study, the analysis of data obtained from a number of 365 participants showed that students' perceived classroom assessment environment in the Romanian Language and Literature subject matter in high school is a significant predictor of the emotions experienced by students during learning this subject for baccalaureate exam, beyond the effect of autonomous motivation and previous academic performance. The results showed that perceived learning-oriented assessment environment was positively correlated with students' autonomous motivation. Moreover, it proved to be a positive predictor for the enjoyment in learning, and a negative one for anger and hopelessness, while its correlation with anxiety or boredom was not significant. In contrast, the perceived performance-oriented assessment environment was uncorrelated with students' autonomous motivation and enjoyment, but was confirmed as a positive predictor of anxiety and boredom experienced during individual learning. Finally, the results and some educational implications are discussed."

Self-regulated pedagogical guidance for out-of-class listening practice: an empirical study of Japanese EFL learners

ABSTRACT Purpose This study proposed a metacognition-inclusive self-regulated learning (SRL) approach to out-of-class listening practice and explored its impact on learners’ listening performance and their reported use of self-regulatory listening strategies. Design/methodology/approach Participants comprised 45 students learning English at a university in Japan. They were drawn from two intact classes and assigned to intervention (IG) and comparison (CG) groups. They engaged in out-of-class listening practice for eight weeks. Only the IG received instruction to employ strategies that focused on metacognitive dimension of self-regulatory listening processes. Listening performance was measured using listening tests before and after the intervention. Strategy use was assessed via a questionnaire at the beginning of the intervention, immediately after the intervention, and nine weeks after the intervention. Findings Both groups made significant gains in the listening tests, and the advantage of the IG over the CG on the listening tests was not significant. However, the IG, but not the CG, demonstrated significant changes in the reported use of strategies over time. Furthermore, the effectiveness of the intervention seemed to depend on learners’ proficiency levels. The results suggest that learners, particularly those with higher proficiency, may engage in more metacognitive SRL processes in an independent listening context through a pedagogical intervention. Originality/value This study demonstrated the efficacy of the newly introduced SRL approach to listening pedagogy, thereby contributing further insight into pedagogical approaches to cultivate self-regulated listeners in independent learning settings.