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Open Learner Models for Multi-activity Educational Systems

  • 2021
  • OriginalPaper
  • Chapter
Published in:
Authors
Solmaz Abdi
Hassan Khosravi
Shazia Sadiq
Ali Darvishi
Published in
Artificial Intelligence in Education
Publisher
Springer International Publishing

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Abstract

The chapter delves into the challenges of learner modelling in educational systems that engage students in diverse activities beyond assessment items. It introduces the Multi-Activity Elo-based learner model (MA-Elo), an extension of the multivariate Elo-based system, designed to track students' knowledge states and item difficulty through various learning activities. MA-Elo employs interpretable methods to estimate students' mastery and item difficulty, utilizing data from activities such as creating, evaluating, and attempting items. The model was evaluated using historical data from the RiPPLE educational system, demonstrating superior predictive performance compared to existing learner models. The chapter highlights the potential of open learner models in enhancing student learning through engagement with multiple activities, paving the way for future research on the impact of such models on self-regulation and student outcomes.
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previous chapter Scrutability, Control and Learner Models: Foundations for Learner-Centred Design in AIED
next chapter Personal Vocabulary Recommendation to Support Real Life Needs
Title
Open Learner Models for Multi-activity Educational Systems
Authors
Solmaz Abdi
Hassan Khosravi
Shazia Sadiq
Ali Darvishi
Copyright Year
2021
Book
Artificial Intelligence in Education

Print ISBN: 978-3-030-78269-6

Electronic ISBN: 978-3-030-78270-2

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-78270-2_2
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