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Impact of Different Pedagogical Agents’ Adaptive Self-regulated Prompting Strategies on Learning with MetaTutor

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Artificial Intelligence in Education (AIED 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7926))

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Abstract

Extended interactions with a pedagogical agent (PA) assisting students to enact cognitive and metacognitive self-regulated processes requires the system to adapt the types and frequency of scaffolding. We compared learners’ perception of PAs’ prompts with MetaTutor, a hypermedia adaptive learning environment, with 40 undergraduates randomly assigned to one of three conditions: non-adaptive prompting (NP), frequency-based adaptive prompting (FP) and frequency and quality-based adaptive prompting (FQP). Results indicate learners are unable to reliably perceive differences in the number of prompts received, though these differences are reflected in positive outcomes in terms of SRL processes enacted and learning gains, and negative outcomes in terms of self-reported satisfaction. Preliminary results indicated that more frequent, but adaptive prompting is an efficient scaffolding strategy, despite negatively impacting learners’ satisfaction.

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References

  1. Graesser, A.C., Conley, M.W., Olney, A.M.: Intelligent tutoring systems. In: Graham, S., Harris, K. (eds.) APA Educational Psychology Handbook: Applications to Learning and Teaching, Washington, DC, vol. 3, pp. 451–473 (2012)

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© 2013 Springer-Verlag Berlin Heidelberg

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Bouchet, F., Harley, J.M., Azevedo, R. (2013). Impact of Different Pedagogical Agents’ Adaptive Self-regulated Prompting Strategies on Learning with MetaTutor. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds) Artificial Intelligence in Education. AIED 2013. Lecture Notes in Computer Science(), vol 7926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39112-5_120

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  • DOI: https://doi.org/10.1007/978-3-642-39112-5_120

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39111-8

  • Online ISBN: 978-3-642-39112-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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