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Investigating Student Interest and Engagement in Game-Based Learning Environments

  • Jiayi Zhang
  • , Stephen Hutt
  • , Jaclyn Ocumpaugh
  • , Nathan Henderson
  • , Alex Goslen
  • , Jonathan P. Rowe
  • , Kristy Elizabeth Boyer
  • , Eric Wiebe
  • , Bradford Mott
  • , James Lester

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

As a cognitive and affective state, interest promotes engagement, facilitates self-regulated learning, and is positively associated with learning outcomes. Research has shown that interest interacts with prior knowledge, but few studies have investigated these issues in the context of adaptive game-based learning environments. Using three subscales from the User Engagement Scale, we examine data from middle school students (N = 77) who interacted with Crystal Island in their regular science class to explore the relationship between interest, knowledge, and learning. We found that interest is significantly related to performance (both knowledge assessment and game completion), suggesting that students with high interest are likely to perform better academically, but also be more engaged in the in-game objectives. These findings have implications both for designers who seek to identify students with lower interest and for those who hope to create adaptive supports.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 23rd International Conference, AIED 2022, Proceedings
EditorsMaria Mercedes Rodrigo, Noburu Matsuda, Alexandra I. Cristea, Vania Dimitrova
PublisherSpringer Science and Business Media Deutschland GmbH
Pages711-716
Number of pages6
ISBN (Print)9783031116438
DOIs
StatePublished - 2022
Externally publishedYes
Event23rd International Conference on Artificial Intelligence in Education, AIED 2022 - Durham, United Kingdom
Duration: Jul 27 2022 → Jul 31 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13355 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Artificial Intelligence in Education, AIED 2022
Country/TerritoryUnited Kingdom
CityDurham
Period7/27/22 → 7/31/22

Bibliographical note

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

Keywords

  • Interest
  • Learning technology
  • Science learning

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