The effects of group metacognitive scaffolding on group metacognitive behaviors, group performance, and cognitive load in computer-supported collaborative learning
Abstract
Previous studies have reported the importance of metacognition on learning performance. However, little effort has been made to develop group metacognitive scaffolding (GMS) in computer-supported collaborative learning (CSCL) environments. The present study sought to extend current understandings of scaffolding in CSCL, by examining the effects of GMS on group metacognitive behavior, group performance, and cognitive load in CSCL environments. In total, 111 college students participated in the study. Participants were divided into small groups and assigned to experimental and control conditions. Students in the experimental group received GMS during an online collaborative learning process, while those in the control group performed online collaborative learning without GMS. The results indicated that GMS had significant impacts on group metacognitive behavioral transition and group performance. Moreover, GMS did not increase students' cognitive load. The results of this study and their implications for teachers and developers are discussed.
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User studies reveal a range of usability challenges around prompting, evaluating and relying on outputs, and deciding on an automation strategy.
“User studies reveal a range of usability challenges around prompting [208], evaluating and relying on outputs [156], and deciding on an automation strategy: whether and how to integrate GenAI into workflows [14,154].”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [208]
GenAI systems present usability challenges around prompting, evaluating and relying on outputs, and optimizing workflows.
“Generative AI (GenAI) systems offer unprecedented opportunities for transforming professional and personal work, yet present challenges around prompting, evaluating and relying on outputs, and optimizing workflows.”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [208]
That participants in [208] avoided effective prompt designs even after encouragement suggests this is partly a metacognitive failure to notice and/or adjust their mental model of the system, signaling low metacognitive flexibility.
“However, that participants in [208]”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [208]
Participants in [208] struggled with prompt iteration: they were unable to choose the right prompting instructions, incorrectly expecting human capabilities, underestimating system capabilities, and insisted on socially appropriate rather than effective prompting.
“Participants in [208] struggled with this (see also [43,85,205]).They were unable to choose the right prompting instructions, incorrectly expecting human capabilities; in some cases, underestimating the system's capabilities; and insisted on socially appropriate-rather than effective-ways of prompting.”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [208]
In [208], non-expert participants using an LLM-based tool to improve a chatbot experienced a struggle getting started.
“In [208], non-expert participants used an LLM-based tool to improve a chatbot through prompting.One of the challenges they experienced was a struggle getting started.7”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [208]
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References 78 · Cited by 117
- Authors
- Zheng, L., Li, X., Zhang, X., & Sun, W.
- Affiliations
- Beijing Normal University (CN)
- Corresponding author
- Zheng, Lanqin
- Venue
- The Internet and Higher Education
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 42
- Pages
- 13-24
- ISSN
- 1096-7516 (ISSN-L)
- OpenAlex
- W2921111799
- Cited by
- 117
- References
- 78
- Citations by year
- 2026: 16 · 2025: 18 · 2024: 22 · 2023: 17 · 2022: 17 · 2021: 21 · 2020: 6
- FWCI
- 19.98
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Internet and Higher Education (publishedVersion)
- Funders
- Thirteenth Five-Year Plan for Educational Science in Beijing (CAHA18089)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Keywords
- metacognition, computer-supported collaborative learning, group performance, cognitive load, online collaborative learning, metacognitive behavior, university students
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