Can adaptive pedagogical agents’ prompting strategies improve students’ learning and self-regulation?

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Abstract

This study examines whether an ITS that fosters the use of metacognitive strategies can benefit from variations in its prompts based on learners’ self-regulatory behaviors. We use log files and questionnaire data from 116 participants who interacted with MetaTutor, an advanced multi-agent learning environment that helps learners to develop their self-regulated learning (SRL) skills, in 3 conditions: one without adaptive prompting (NP), one with fading prompts based on learners’ deployment SRL processes (FP), and one where prompts can also increase if learners fail to deploy SRL processes adequately (FQP). Results indicated that an initially more frequent but progressively fading prompting strategy is beneficial to learners’ deployment of SRL processes once the scaffolding is faded, and has no negative impact on learners’ perception of the system’s usefulness. We also found that increasing the frequency of prompting was not sufficient to have a positive impact on the use of SRL processes, when compared to FP. These results provide insights on parameters relevant to prompting adaptation strategies to ensure transfer of metacognitive skills beyond the learning session.

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Bouchet, F., Harley, J. M., & Azevedo, R. (2016). Can adaptive pedagogical agents’ prompting strategies improve students’ learning and self-regulation? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9684, pp. 368–374). Springer Verlag. https://doi.org/10.1007/978-3-319-39583-8_43

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