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Computer‐based scaffoldings influence students' metacognitive monitoring and problem‐solving efficiency in an intelligent tutoring system.

  • Published In: Journal of Computer Assisted Learning, 2023, v. 39, n. 5. P. 1652 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Wang, Tingting; Zheng, Juan; Tan, Chengyi; Lajoie, Susanne P. 3 of 3

Abstract

Background: Computer‐based scaffolding has been intensively used to facilitate students' self‐regulated learning (SRL). However, most previous studies investigated how computer‐based scaffoldings affected the cognitive aspect of SRL, such as knowledge gains and understanding levels. In contrast, more evidence is needed to examine the effects of scaffolding on the metacognitive dimension and efficiency outcome of SRL. Objectives: This study aims to examine the role of computer‐based scaffolding in students' metacognitive monitoring and problem‐solving efficiency. Methods: Seventy‐two medical students completed two clinical reasoning tasks in BioWorld, an intelligent tutoring system (ITS) designed for promoting medical students' diagnostic expertise. During solving the tasks, students were asked to report their confidence judgements about proposed diagnoses. Computer trace data were used to identify task completion time (CT) and students' use of three scaffolding types, that is, conceptual, strategic, and metacognitive. Then we calculated students' metacognitive monitoring accuracy (i.e., calibration) and problem‐solving efficiency. Results and Conclusions: One‐sample t‐test demonstrated that students inaccurately monitored their learning processes and were overconfident in both tasks. Linear mixed‐effects models (LMMs) indicated that the intensive use of metacognitive scaffolding positively predicted students' metacognitive monitoring accuracy. Moreover, strategic scaffolding was negatively related to problem‐solving efficiency, whereas metacognitive scaffolding positively influenced problem‐solving efficiency. Takeaways: This study shows the importance of metacognitive scaffolding in improving the accuracy of metacognitive monitoring and problem‐solving efficiency. Findings from this study provide new insights for instructors and ITS developers to optimise the design of scaffoldings. Lay Description: What is already known about this topic?: Computer‐based scaffolding can facilitate students' knowledge gains and academic performance during self‐regulated learning (SRL).The effects of computer‐based scaffolding on the metacognitive dimension and efficiency outcome of SRL are still in a nascent phase. What this paper adds?: This paper explores how different types of computer‐based scaffolding affect students' metacognitive monitoring and problem‐solving efficiency.Metacognitive scaffolding improved the accuracy of medical students' confidence judgements.Metacognitive scaffolding promoted medical students' diagnostic problem‐solving efficiency.Strategic scaffolding had a negative effect on problem‐solving efficiency. Implications for practice: Instructors could provide more metacognitive scaffoldings to facilitate students' metacognitive monitoring accuracy.The designers of intelligent tutoring systems and instructors should consider the costs associated with using scaffoldings. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Computer Assisted Learning. 2023/10, Vol. 39, Issue 5, p1652
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2023
  • ISSN:0266-4909
  • DOI:10.1111/jcal.12824
  • Accession Number:171903683
  • Copyright Statement:Copyright of Journal of Computer Assisted Learning is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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