Volume 27 Number 1, 2023 Applying educational data mining to explore individual experiences in digital games

Applying educational data mining to explore individual experiences in digital games

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bitstream:
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collection:
Volume 27 Number 1, 2023
contributor.author:
Poole, Frederick J. Clarke-Midura, Jody
date.accessioned:
2023-08-05T19:59:14Z
date.available:
2023-08-05T19:59:14Z
date.copyright:
2023
date.issued:
2023-08-07
description.abstract:
Research involving digital games and language learning is rapidly growing. One advantage of using digital games to support language learning is the ability to collect data on students learning in real time. In this study, we use educational data mining methods to explore the relationship between in-game data and elementary students’ Chinese language learning. Thirty-six students in the sixth grade played a digital game for eight 25-minute sessions as part of their Chinese Dual Language Immersion classroom instruction. We used classification and regression tree analyses and cluster analyses to explore how in- game indicators, such as battles, time spent reading a text, and the use of an in-game glossing tool are associated with language learning and change in affect. The results indicate that time on task and use of the glossing tool were the most important variables in determining language learning gains. We also identified four subgroups of gameplay styles. While there were no significant differences in learning or affective factors based on the subgroups, these gameplay styles allow for a more individualized approach to analyzing learning within digital environments
endingpage:
26
format.extent:
26
identifier.citation:
Poole, F. J., & Clarke-Midura, J. (2023). Applying educational data mining to explore individual experiences in digital games. Language Learning & Technology, 27(1), 1–26. http://hdl.handle.net/10125/73522
identifier.issn:
1094-3501
identifier.uri:
https://hdl.handle.net/10125/73522
number:
1
publicationname:
Language Learning & Technology
publisher:
University of Hawaii National Foreign Language Resource Center Center for Language & Technology
rights.license:
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
rights.uri:
https://creativecommons.org/licenses/by-nc-nd/4.0/
site_url:
/item/10125-73522/
startingpage:
1
subject:
Educational Data Mining, Game-based Language Learning, Chinese as a Foreign Language
title:
Applying educational data mining to explore individual experiences in digital games
type:
Article Text
volume:
27