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Game-Based Learning for Asynchronous AI Literacy Course: Approach to Improve Students' Cognitive, Behavioural, Affective, and Ethical Learning of AI

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Title: Game-Based Learning for Asynchronous AI Literacy Course: Approach to Improve Students' Cognitive, Behavioural, Affective, and Ethical Learning of AI
Language: English
Authors: Jinhee Kim (ORCID 0000-0002-3365-7354), Guang Yang, Wing Sha Chan, Xi Lin (ORCID 0000-0003-2387-4117), Yukyeong Song, Na Li (ORCID 0000-0003-2395-3499)
Source: European Journal of Education. 2026 61(2).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 16
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Tests/Questionnaires
Education Level: Higher Education
Postsecondary Education
Descriptors: Game Based Learning, Asynchronous Communication, Artificial Intelligence, Digital Literacy, Higher Education, Required Courses, College Freshmen, Cognitive Processes, Affective Behavior, Student Behavior, Ethics, Student Attitudes
DOI: 10.1111/ejed.70658
ISSN: 0141-8211
1465-3435
Abstract: Educators in higher education face persistent challenges in scaling AI literacy across disciplines and helping novice learners understand abstract AI concepts. Although research on game-based learning (GBL) reports mixed outcomes, few studies have examined its large-scale use in mandatory, asynchronous AI literacy courses for diverse undergraduate populations. Addressing this gap, this study investigates a scalable GBL-based AI literacy course delivered to 4898 first-year undergraduates across disciplines. Using a mixed-methods design with 311 valid pre- and post-survey responses and 20 interviews, the study evaluates students' cognitive, behavioural, affective, and ethical learning of AI. Quantitative results show significant improvements in overall AI literacy across cognitive, behavioural, and affective dimensions, while ethical learning gains were not statistically significant. Qualitative findings suggest that GBL stimulated students' epistemic curiosity and engagement with AI ethics while revealing pedagogical, technical, and learner-centered challenges. The study provides large-scale empirical evidence and proposes an instructional design framework for scalable AI literacy integration in higher education.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1506840
Database: ERIC
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  Data: Game-Based Learning for Asynchronous AI Literacy Course: Approach to Improve Students' Cognitive, Behavioural, Affective, and Ethical Learning of AI
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  Data: <searchLink fieldCode="AR" term="%22Jinhee+Kim%22">Jinhee Kim</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-3365-7354">0000-0002-3365-7354</externalLink>)<br /><searchLink fieldCode="AR" term="%22Guang+Yang%22">Guang Yang</searchLink><br /><searchLink fieldCode="AR" term="%22Wing+Sha+Chan%22">Wing Sha Chan</searchLink><br /><searchLink fieldCode="AR" term="%22Xi+Lin%22">Xi Lin</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2387-4117">0000-0003-2387-4117</externalLink>)<br /><searchLink fieldCode="AR" term="%22Yukyeong+Song%22">Yukyeong Song</searchLink><br /><searchLink fieldCode="AR" term="%22Na+Li%22">Na Li</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2395-3499">0000-0003-2395-3499</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22European+Journal+of+Education%22"><i>European Journal of Education</i></searchLink>. 2026 61(2).
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: <searchLink fieldCode="DE" term="%22Game+Based+Learning%22">Game Based Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Asynchronous+Communication%22">Asynchronous Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+Literacy%22">Digital Literacy</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Required+Courses%22">Required Courses</searchLink><br /><searchLink fieldCode="DE" term="%22College+Freshmen%22">College Freshmen</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Affective+Behavior%22">Affective Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Behavior%22">Student Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Ethics%22">Ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink>
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  Data: 10.1111/ejed.70658
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  Data: 0141-8211<br />1465-3435
– Name: Abstract
  Label: Abstract
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  Data: Educators in higher education face persistent challenges in scaling AI literacy across disciplines and helping novice learners understand abstract AI concepts. Although research on game-based learning (GBL) reports mixed outcomes, few studies have examined its large-scale use in mandatory, asynchronous AI literacy courses for diverse undergraduate populations. Addressing this gap, this study investigates a scalable GBL-based AI literacy course delivered to 4898 first-year undergraduates across disciplines. Using a mixed-methods design with 311 valid pre- and post-survey responses and 20 interviews, the study evaluates students' cognitive, behavioural, affective, and ethical learning of AI. Quantitative results show significant improvements in overall AI literacy across cognitive, behavioural, and affective dimensions, while ethical learning gains were not statistically significant. Qualitative findings suggest that GBL stimulated students' epistemic curiosity and engagement with AI ethics while revealing pedagogical, technical, and learner-centered challenges. The study provides large-scale empirical evidence and proposes an instructional design framework for scalable AI literacy integration in higher education.
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  Data: 2026
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      – SubjectFull: Asynchronous Communication
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      – SubjectFull: Artificial Intelligence
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