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Article: Maximizing learning without sacrificing the fun: Stealth assessment, adaptivity and learning supports in educational games

TitleMaximizing learning without sacrificing the fun: Stealth assessment, adaptivity and learning supports in educational games
Authors
Keywordsadaptivity
game-based learning
learning supports
stealth assessment
STEM education
Issue Date2021
Citation
Journal of Computer Assisted Learning, 2021, v. 37, n. 1, p. 127-141 How to Cite?
AbstractIn this study, we investigated the validity of a stealth assessment of physics understanding in an educational game, as well as the effectiveness of different game-level delivery methods and various in-game supports on learning. Using a game called Physics Playground, we randomly assigned 263 ninth- to eleventh-grade students into four groups: adaptive, linear, free choice and no-treatment control. Each condition had access to the same in-game learning supports during gameplay. Results showed that: (a) the stealth assessment estimates of physics understanding were valid—significantly correlating with the external physics test scores; (b) there was no significant effect of game-level delivery method on students' learning; and (c) physics animations were the most effective (among eight supports tested) in predicting both learning outcome and in-game performance (e.g. number of game levels solved). We included student enjoyment, gender and ethnicity in our analyses as moderators to further investigate the research questions.
Persistent Identifierhttp://hdl.handle.net/10722/318855
ISSN
2023 Impact Factor: 5.1
2023 SCImago Journal Rankings: 1.842
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorShute, Valerie-
dc.contributor.authorRahimi, Seyedahmad-
dc.contributor.authorSmith, Ginny-
dc.contributor.authorKe, Fengfeng-
dc.contributor.authorAlmond, Russell-
dc.contributor.authorDai, Chih Pu-
dc.contributor.authorKuba, Renata-
dc.contributor.authorLiu, Zhichun-
dc.contributor.authorYang, Xiaotong-
dc.contributor.authorSun, Chen-
dc.date.accessioned2022-10-11T12:24:43Z-
dc.date.available2022-10-11T12:24:43Z-
dc.date.issued2021-
dc.identifier.citationJournal of Computer Assisted Learning, 2021, v. 37, n. 1, p. 127-141-
dc.identifier.issn0266-4909-
dc.identifier.urihttp://hdl.handle.net/10722/318855-
dc.description.abstractIn this study, we investigated the validity of a stealth assessment of physics understanding in an educational game, as well as the effectiveness of different game-level delivery methods and various in-game supports on learning. Using a game called Physics Playground, we randomly assigned 263 ninth- to eleventh-grade students into four groups: adaptive, linear, free choice and no-treatment control. Each condition had access to the same in-game learning supports during gameplay. Results showed that: (a) the stealth assessment estimates of physics understanding were valid—significantly correlating with the external physics test scores; (b) there was no significant effect of game-level delivery method on students' learning; and (c) physics animations were the most effective (among eight supports tested) in predicting both learning outcome and in-game performance (e.g. number of game levels solved). We included student enjoyment, gender and ethnicity in our analyses as moderators to further investigate the research questions.-
dc.languageeng-
dc.relation.ispartofJournal of Computer Assisted Learning-
dc.subjectadaptivity-
dc.subjectgame-based learning-
dc.subjectlearning supports-
dc.subjectstealth assessment-
dc.subjectSTEM education-
dc.titleMaximizing learning without sacrificing the fun: Stealth assessment, adaptivity and learning supports in educational games-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/jcal.12473-
dc.identifier.scopuseid_2-s2.0-85088557445-
dc.identifier.volume37-
dc.identifier.issue1-
dc.identifier.spage127-
dc.identifier.epage141-
dc.identifier.eissn1365-2729-
dc.identifier.isiWOS:000552754700001-

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