The relationship between students' self‐regulated learning behaviours and problem‐solving efficiency in technology‐rich learning environments.
Background: Scholars have confirmed the vital roles of self‐regulated learning (SRL) behaviours in predicting task performance, especially within non‐linear technology‐rich learning environments (TREs). However, few studies focused on the learning costs (e.g., study effort and time‐on‐task) related...
| Publicado en: | Journal of Computer Assisted Learning Vol. 40; no. 6; pp. 2886 - 2901 |
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| Autores principales: | , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Dec2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=180899675&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 180899675 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Dec2024 vid: 40 iid: 6 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 180899675 178553810 180899675 180899675 10.1111/jcal.13043 180899675 ppf: 2886 ppct: 15 formats: tig: atl: The relationship between students' self‐regulated learning behaviours and problem‐solving efficiency in technology‐rich learning environments. aug: au: Wang, Tingting Ruiz‐Segura, Alejandra Li, Shan Lajoie, Susanne P. affil: School of Education, Renmin University of China, Beijing, China sug: subj: Students, Medical Psychosocial Factors Problem Solving Evaluation Learning Environment Self-Directed Learning Evaluation Task Performance and Analysis Human Adult Patient Simulation Time Factors Information Technology Funding Source Male Female Structural Equation Modeling Software Confidence Judgment Feedback Clinical Reasoning Cluster Analysis T-Tests Algorithms Reflection Post Hoc Analysis Adult: 19-44 years Male Female ab: Background: Scholars have confirmed the vital roles of self‐regulated learning (SRL) behaviours in predicting task performance, especially within non‐linear technology‐rich learning environments (TREs). However, few studies focused on the learning costs (e.g., study effort and time‐on‐task) related to SRL and the efficiency outcome of SRL (i.e., the relative relationship between learning costs and performance). Objectives: This study examined the relationship between students' SRL behaviours and problem‐solving efficiency in the context of TREs. Methods: Eighty‐two medical students accomplished a diagnostic task in a computer‐simulated environment, and they were classified into the efficient or less efficient group according to diagnostic performance and time‐on‐task. Then we coded students' SRL behaviours from trace data and counted the frequency of each SRL behaviour. The recurrence quantification and lag sequential analyses were performed to extract the dynamic characteristics of SRL behaviours, including recurrent patterns and sequential transitions. Results and Conclusions: Efficient students conducted more frequent Self‐reflection behaviours than the less efficient. For the recurrent patterns, efficient students tended to exhibit longer SRL behaviour sequences comprising a variety of different SRL behaviours (e.g., Task Analysis > Add Test > Add Hypotheses > Categorise Evidence) as well as longer sequences of repeated SRL behaviours (e.g., Add Test > Add Test > Add Test > Add Test). Moreover, efficient students exhibited more sequential transitions between different SRL behaviours than less efficient. Takeaways: Overall, this study revealed the effects of SRL on problem‐solving efficiency, which inspired researchers to incorporate problem‐solving efficiency as an evaluation criterion of SRL processes. Lay Description: What is already known about this topic?: Previous studies have highlighted the importance of self‐regulated learning (SRL) behaviours in facilitating students' performance.SRL behaviours also affect learning costs, such as cognitive effort and study time.SRL behaviours influence both learning costs and outcomes and thus their relative relationship, that is, problem‐solving efficiency.Efficient problem‐solvers can achieve high performance with low effort and vice versa. What this paper adds?: Efficient problem‐solvers conducted more self‐reflection behaviours than less efficient.Efficient problem‐solvers repeated longer SRL behaviour sequences than less efficient.Efficient problem‐solvers repeated the same SRL behaviour before moving forward to a different behaviour.Efficient problem‐solvers transitioned between different SRL behaviours more frequently than less efficient. Implications for practice: Instructors should design appropriate metacognitive prompts to facilitate students' self‐reflection and thus problem‐solving efficiency.Intelligent tutoring systems can generate real‐time feedback based on students' SRL features to improve problem‐solving efficiency. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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