Abstract: D. A. Dever, N. A. Sonnenfeld, M. D. Wiedbusch, S. G. Schmorrow, M. J. Amon, R. Azevedo (2023)

Self-regulated learning (SRL), learnersâ€™ monitoring and control of cognitive, affective, metacognitive, and motivational processes, is essential for learning. However, cognitive and metacognitive SRL strategies are not typically used accurately leading to poor learning outcomes. Intelligent tutoring systems (ITSs) attempt to address this issue by prompting and scaffolding learners to engage in SRL via using pedagogical agents. However, current literature does not examine the extent to which learnersâ€™ deployed strategies are functional or dysfunctional in relation to pedagogical agent scaffolding. The current study collected 117 undergraduate studentsâ€™ data as they learned with MetaTutor, an ITS about the human circulatory system. Participants were randomly assigned to either the (1) Prompt and Feedback Condition where pedagogical agents scaffolded cognitive and metacognitive SRL strategies or (2) Control Condition where no prompts or feedback were provided. Results demonstrated that learners who received prompts by the pedagogical agents to engage in SRL had higher learning gains as well as greater frequencies across most strategies compared to those in the Control Condition who relied on self-initiated strategy use. While sequential transitions across all strategies were not significant between conditions, further analysis grounded in Complex Systems Theory found that learners who were prompted to engage in strategies demonstrated a significantly lower degree of repetition and balance between repetitive and novel patterns of strategy use. The findings suggest that pedagogical agents within MetaTutor successfully scaffolded the functional deployment of cognitive and metacognitive SRL strategies and are indicative of higher learning after interacting with ITSs.

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A complex systems approach to analyzing pedagogical agentsâ€™ scaffolding of self-regulated learning within an intelligent tutoring system