Intelligent tutoring systems (ITSs) incorporate pedagogical agents (PAs) to scaffold learners' self‐regulated learning (SRL) via prompts and feedback to promote learners' monitoring and regulation of their cognitive, affective, metacognitive and motivational processes to achieve their (sub)goals. This study examines PAs' effectiveness in scaffolding and teaching SRL during learning with MetaTutor, an ITS on the human circulatory system. Undergraduates ( Most learners struggle to efficiently and effectively use self‐regulated learning (SRL) strategies to attain goals and subgoals. There is a need for SRL to be scaffolded for learners to manage multiple goals and subgoals while learning about complex STEM topics. Intelligent tutoring systems (ITSs) typically incorporate pedagogical agents (PAs) to prompt learners to engage in SRL strategy and provide feedback. There are mixed findings on the effectiveness of PAs in scaffolding learners' SRL. We consider PAs not only scaffolders but also teachers of SRL. Results showed that while PAs encouraged the use of SRL strategies when the content was relevant to subgoals, they did not discourage the use of SRL strategies when the content was not relevant. Results for this study were mixed in their support of PAs as teachers of SRL. Learners increasingly depended on PAs to prompt SRL strategies as time on task progressed. PAs are effective scaffolders of SRL with more research needed to understand their role as teachers of SRL. PA scaffolding is more essential as time on task progresses. When deploying specific cognitive and metacognitive SRL strategies, the relevance of the content to learners' subgoals should be taken into account.
This content will become publicly available on May 31, 2024
Capturing evidence for dynamic changes in self‐regulated learning (SRL) behaviours resulting from interventions is challenging for researchers. In the current study, we identified students who were likely to do poorly in a biology course and those who were likely to do well. Then, we randomly assigned a portion of the students predicted to perform poorly to a science of learning to learn intervention where they were taught SRL study strategies. Learning outcome and log data (257 K events) were collected from
What is already known about this topic Self‐regulated learning (SRL) knowledge and skills are strong predictors of postsecondary STEM student success. SRL is a dynamic, temporal process that leads to purposeful student engagement. Methods and metrics for measuring dynamic SRL behaviours in learning contexts are needed. What this paper adds A Markov process for measuring dynamic SRL processes using log data. Evidence that dynamic, interaction‐dominant aspects of SRL predict student achievement. Evidence that SRL processes can be meaningfully impacted through educational intervention. Implications for theory and practice Complexity approaches inform theory and measurement of dynamic SRL processes. Static representations of dynamic SRL processes are promising learning analytics metrics. Engineered features of LMS usage are valuable contributions to AI models.
- Award ID(s):
- 1821601
- NSF-PAR ID:
- 10419812
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- British Journal of Educational Technology
- Volume:
- 54
- Issue:
- 5
- ISSN:
- 0007-1013
- Page Range / eLocation ID:
- p. 1204-1221
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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A design based research study using actor network theory highlighting the limitations of Connected Spaces in sparking notable behaviour change among students by itself but being retooled as a teacher support tool in enabling cross‐group collaborations.
Presenting conceptions of collaboration through technologies as bridging agentic gaps and acting with new agencies in performing help‐seeking related actions.
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