Affect sequences and learning in Betty's brain

Juliana Ma Alexandra L. Andres, Luc Paquette, Jaclyn Ocumpaugh, Yang Jiang, Ryan S. Baker, Shamya Karumbaiah, Stefan Slater, Nigel Bosch, Anabil Munshi, Allison Moore, Gautam Biswas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Education research has explored the role of students' affective states in learning, but some evidence suggests that existing models may not fully capture the meaning or frequency of how students transition between different states. In this study we examine the patterns of educationally-relevant affective states within the context of Betty's Brain, an open-ended, computer-based learning system used to teach complex scientific processes. We examine three types of affective transitions based on similarity with the theorized D'Mello and Graesser model, transition between two affective states, and the sustained instances of certain states. We correlate of the frequency of these patterns with learning outcomes and our findings suggest that boredom is a powerful indicator of students' knowledge, but not necessarily indicative of learning. We discuss our findings within the context of both research and theory on affect dynamics and the implications for pedagogical and system design.

Original languageEnglish (US)
Title of host publicationProceedings of the 9th International Conference on Learning Analytics and Knowledge
Subtitle of host publicationLearning Analytics to Promote Inclusion and Success, LAK 2019
PublisherAssociation for Computing Machinery,
Pages383-390
Number of pages8
ISBN (Electronic)9781450362566
DOIs
StatePublished - Mar 4 2019
Event9th International Conference on Learning Analytics and Knowledge, LAK 2019 - Tempe, United States
Duration: Mar 4 2019Mar 8 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference9th International Conference on Learning Analytics and Knowledge, LAK 2019
CountryUnited States
CityTempe
Period3/4/193/8/19

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Keywords

  • Affect
  • Affect dynamics
  • Learning analytics

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Andres, J. M. A. L., Paquette, L., Ocumpaugh, J., Jiang, Y., Baker, R. S., Karumbaiah, S., Slater, S., Bosch, N., Munshi, A., Moore, A., & Biswas, G. (2019). Affect sequences and learning in Betty's brain. In Proceedings of the 9th International Conference on Learning Analytics and Knowledge: Learning Analytics to Promote Inclusion and Success, LAK 2019 (pp. 383-390). (ACM International Conference Proceeding Series). Association for Computing Machinery,. https://doi.org/10.1145/3303772.3303807