Use Of Self-regulated Learning Processes Research Articles

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.

Tracking Changes in Students’ Online Self-Regulated Learning Behaviors and Achievement Goals Using Trace Clustering and Process Mining

Success in online and blended courses requires engaging in self-regulated learning (SRL), especially for challenging STEM disciplines, such as physics. This involves students planning how they will navigate course assignments and activities, setting goals for completion, monitoring their progress and content understanding, and reflecting on how they completed each assignment. Based on Winne & Hadwin’s COPES model, SRL is a series of events that temporally unfold during learning, impacted by changing internal and external factors, such as goal orientation and content difficulty. Thus, as goal orientation and content difficulty change throughout a course, so might students’ use of SRL processes. This paper studies how students’ SRL behavior and achievement goal orientation change over time in a large (N = 250) college introductory level physics course taught online. Students’ achievement goal orientation was measured by repeated administration of the achievement goals questionnaire-revised (AGQ-R). Students’ SRL behavior was measured by analyzing their clickstream event traces interacting with online learning modules via a combination of trace clustering and process mining. Event traces were first divided into groups similar in nature using agglomerative clustering, with similarity between traces determined based on a set of derived characteristics most reflective of students’ SRL processes. We then generated causal nets for each cluster of traces via process mining and interpreted the underlying behavior and strategy of each causal net according to the COPES SRL framework. We then measured the frequency at which students adopted each causal net and assessed whether the adoption of different causal nets was associated with responses to the AGQ-R. By repeating the analysis for three sets of online learning modules assigned at the beginning, middle, and end of the semester, we examined how the frequency of each causal net changed over time, and how the change correlated with changes to the AGQ-R responses. Results have implications for measuring the temporal nature of SRL during online learning, as well as the factors impacting the use of SRL processes in an online physics course. Results also provide guidance for developing online instructional materials that foster effective SRL for students with different motivational profiles.

"Because I'm Bad at the Game!" A Microanalytic Study of Self Regulated Learning in League of Legends.

Self-regulated learning (SRL) is a form of learning guided by the student's own meta-cognition, motivation, and strategic action, often in the absence of an educator. The use of SRL processes and skills has been demonstrated across numerous academic and non-academic contexts including athletics. However, manifestation of these processes within esports has not been studied. Similar to traditional athletes, esports players' performance is likely correlated with their ability to engage SRL skills as they train. Thus, the study of SRL in the context of esports would be valuable in supporting players' learning and mastery of play through specialized training and computational support. Further, an understanding of how SRL manifests in esports would highlight new opportunities to use esports in education. Existing work on SRL in games, however, predominantly focuses on educational games. In this work, we aim to take a first step in the study of SRL in esports by replicating Kitsantas and Zimmerman's (2002) volleyball study in the context of League of Legends. We compared the self-regulatory processes of expert, non-expert, and novice League of Legends players, and found that there were significant differences for processes in the forethought phase. We discuss three implications of these findings: what they mean for the development of future computational tools for esports players, implications that esports may be able to teach SRL skills that transfer to academics, and what educational technology can learn from esports to create more effective tools.

Self-regulated learning microanalysis for the study of the performance of clinical examinations by physiotherapy students

BackgroundStudents require feedback on their self-regulated learning (SRL) processes to improve the performance of clinical examinations. The key SRL processes used by students can be identified by SRL-micro-analysis but, this method has not been previously applied to physiotherapy students. The aim of this pilot study was to test a research design that might allow the evaluation of the potential usefulness of SRL microanalysis for the identification of key SRL processes used by physiotherapy students during the performance of a clinical examination skill. The objectives of the pilot study were: 1) to evaluate whether SRL-microanalysis could identify differences in the use of SRL processes between successful and unsuccessful students; 2) to evaluate the reliability of SRL microanalysis ratings produced by different assessors.MethodsSRL-microanalysis was used with second year physiotherapy students of a Spanish university (n = 26) as they performed a goniometric task. The task required students to obtain a goniometric measurement of the shoulder joint of a peer. Two assessors evaluated student performance and conducted the SRL- microanalysis with all students. An analysis of inter-rater reliability was performed to evaluate the degree of agreement between assessors.ResultsThe SRL-microanalysis revealed differences in the use of key SRL processes between successful (n = 15: 57.0%) and unsuccessful performers (n = 11: 43.0%): The differences were particularly evident in strategic planning and self-monitoring skills. There was good inter-rater reliability for scoring of strategic planning (k = 0.792), self-monitoring (k = 0.946) and self-evaluation (k = 0.846).ConclusionThe use of SRL microanalysis characterized the key SRL processes of physiotherapy students performing a clinical skill with reliability between the assessors. This pilot study supports the potential usefulness of SRL-microanalysis for the identification of key SRL processes in physiotherapy education. Therefore, this study paves the way to the development of a full study, with a larger number of students and more diverse clinical tasks, to evaluate the SRL processes in successful and unsuccessful students.

The struggling student: a thematic analysis from the self-regulated learning perspective.

Students who engage in self-regulated learning (SRL) are more likely to achieve academic success compared with students who have deficits in SRL and tend to struggle with academic performance. Understanding how poor SRL affects the response to failure at assessment will inform the development of better remediation. Semi-structured interviews were conducted with 55 students who had failed the final re-sit assessment at two medical schools in the UK to explore their use of SRL processes. A thematic analysis approach was used to identify the factors, from an SRL perspective, that prevented students from appropriately and adaptively overcoming failure, and confined them to a cycle of recurrent failure. Struggling students did not utilise key SRL processes, which caused them to make inappropriate choices of learning strategies for written and clinical formats of assessment, and to use maladaptive strategies for coping with failure. Their normalisation of the experience and external attribution of failure represented barriers to their taking up of formal support and seeking informal help from peers. This study identified that struggling students had problems with SRL, which caused them to enter a cycle of failure as a result of their limited attempts to access formal and informal support. Implications for how medical schools can create a culture that supports the seeking of help and the development of SRL, and improves remediation for struggling students, are discussed.

A Comparative study on Intelligent Tutoring Systems fostering Self Regulated Learning.

Educational data mining is an emerging research area where the traditional data mining techniques are applied on Intelligent Tutoring System (ITS) to study the learning pattern of students. This paper conducts a survey on various ITS that are used currently. An agent-based ITS that fosters the use of Self Regulated Learning (SRL) processes mainly concentrates on two questions: (1) How can students be grouped according to their performance and their type of interaction with the system? (2) How do specific learning behaviors of high and low performing students differ, in particular regarding their use of SRL processes ?.The study helps in understanding how data can be mined and how the learners can be grouped into different clusters based on their learning activities.

Cognitive engagement variations among students of different ability level and sex in a computer problem solving game

The study investigated the cognitive engagement processes used by more and less successful learners in a computer problem solving game. These engagement variations were also related to sex and ability differences among students. Performance and engagement were monitored interactively as students learned a computer problem solving game; student comments and notes were also recorded. Results showed the records of more and less successful students to be distinguished by the spontaneous use of self-regulated learning processes — a sophisticated form of cognitive engagement. More successful students also appeared to shift cognitive engagement levels in response to computer game feedback. Success on the computer task and cognitive engagement variations were correlated with student differences in both ability and sex in this sample.