Instructing students on effective sequences of examples and problems: Does self‐regulated learning improve from knowing what works and why?
Nowadays, students often practice problem‐solving skills in online learning environments with the help of examples and problems. This requires them to self‐regulate their learning. It is questionable how novices self‐regulate their learning from examples and problems and whether they need support. T...
| Publicado en: | Journal of Computer Assisted Learning Vol. 38; no. 1; pp. 19 - 40 |
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| Autores principales: | , , , |
| Formato: | equations & formulas exam questions pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Feb2022
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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=154497182&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 154497182 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Feb2022 vid: 38 iid: 1 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 154497182 151595509 154497182 154497182 10.1111/jcal.12589 154497182 ppf: 19 ppct: 21 formats: tig: atl: Instructing students on effective sequences of examples and problems: Does self‐regulated learning improve from knowing what works and why? aug: au: van Harsel, Milou Hoogerheide, Vincent Verkoeijen, Peter van Gog, Tamara affil: Learning and Innovation Centre, Avans University of Applied Sciences, Breda, the Netherlands sug: subj: Self-Directed Learning Self-Efficacy Problem Solving Online Education Learning Environment Human Students Videorecording Motivation Computer-Assisted Instruction Male Female Adolescence Colleges and Universities Netherlands Netherlands Descriptive Statistics Pearson's Correlation Coefficient Task Performance and Analysis Scales Nonparametric Statistics Wilcoxon Signed Rank Test Mann-Whitney U Test Kruskal-Wallis Test Post Hoc Analysis Adolescent: 13-18 years Male Female ab: Nowadays, students often practice problem‐solving skills in online learning environments with the help of examples and problems. This requires them to self‐regulate their learning. It is questionable how novices self‐regulate their learning from examples and problems and whether they need support. The present study investigated the open questions (1) to what extent students' (novices) task selections align with instructional design principles and (2) whether informing them about these principles would improve their task selections, learning outcomes, and motivation. Higher education students (N = 150) learned a problem‐solving procedure by fixed sequences of examples and problems (FS‐condition), or by self‐regulated learning (SRL). The SRL participants selected tasks from a database, varying in format, complexity, and cover story, either with (ISRL‐condition) or without (SRL‐condition) watching a video detailing the instructional design principles. Students' task‐selection patterns in both SRL conditions largely corresponded to the principles, although tasks were built up in complexity more often in the ISRL‐condition than in the SRL‐condition. Moreover, there was still room for improvement in students' task selections after solving practice problems. The video instruction helped students to better apply certain principles, but did not enhance learning and motivation. Finally, there were no test performance or motivational differences among conditions. Although these findings might suggest it is relatively 'safe' to allow students to independently start learning new problems‐solving tasks using examples and problems, caution is warranted: It is unclear whether these findings generalize to other student populations, as the students participating in this study have had some experience with similar tasks or learning with examples. Moreover, as there was still room for improvement in students' task selections, follow‐up research should investigate how we can further improve self‐regulated learning from examples and practice problems. Lay Description: What is (not) known about the subject matter: Learning new problem‐solving skills online with examples and problems is becoming more commonInstructional design principles (IDP) detail how to sequence tasks to optimize learning and motivationIt is unclear whether students spontaneously adhere to IDP when they select learning tasksNot much is known about how to support students to make better task selections What is the contribution of this paper: Students received a fixed task sequence (FS‐condition) or selected tasks themselves (SRL)Prior to SRL, SRL‐students watched a video about IDP (ISRL‐condition) or not (SRL‐condition)Results showed that (I)SRL‐students' task‐selections matched quite well with IDPThere were no differences among the FS and (I)SRL conditions in performance or motivation What are the implications of the findings: Students were quite capable of self‐regulating their learning from examples and problemsSRL was even as effective, efficient, and motivating as a fixed task sequenceWatching a video on IDP affected students' task‐selections, but did not enhance learning and motivationFuture research should examine how to further support SRL from examples and problems pubtype: Academic Journal doctype: equations & formulas exam questions pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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