Using Self-Determination Theory to Explain How Teacher Support Enhances Student Engagement and Higher-Order Thinking in Simulation-Based Learning with GenAI

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Bibliographic Details
Title: Using Self-Determination Theory to Explain How Teacher Support Enhances Student Engagement and Higher-Order Thinking in Simulation-Based Learning with GenAI
Language: English
Authors: Xueqing Fang (ORCID 0009-0007-1820-8159), Minjie Yang, Xinyan Zhou, Yan Li, Thomas K. F. Chiu
Source: Journal of Educational Computing Research. 2026 64(4):850-882.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 33
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Thinking Skills, Learner Engagement, Teacher Student Relationship, Computer Simulation, Artificial Intelligence, Technology Uses in Education, Undergraduate Students, Psychological Patterns, Student Needs, Student Satisfaction, Foreign Countries, Private Colleges, Business Education, Academic Achievement, Student Attitudes
Geographic Terms: China
DOI: 10.1177/07356331261421079
ISSN: 0735-6331
1541-4140
Abstract: Teacher support significantly influences student engagement and learning outcomes in educational environments that incorporate generative AI (GenAI). Simulation-based learning (SBL) fosters complex skill development but may cause cognitive overload without appropriate instructional support. While GenAI tools provide personalized assistance, their integration into teaching and learning presents pedagogical challenges. Grounded in Self-Determination Theory (SDT), this study investigated the effects of SDT-based teacher support on undergraduates' psychological need satisfaction, engagement, and learning outcomes in a GenAI-assisted simulation-based learning environment. Eighty university students participated in a GenAI-assisted performance management simulation activity and were assigned to conditions with or without teacher support. Our analysis showed that teacher support: (i) significantly enhanced competence and relatedness satisfaction; (ii) significantly increased cognitive, emotional, and agentic engagement; (iii) significantly improved learning performance, problem solving, and critical thinking; and (iv) did not significantly promote autonomy satisfaction, behavioral engagement, or creativity. This study underscores the essential role of teacher support in improving student engagement and higher-order thinking skills in learning contexts incorporating GenAI.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1502302
Database: ERIC
Description
Abstract:Teacher support significantly influences student engagement and learning outcomes in educational environments that incorporate generative AI (GenAI). Simulation-based learning (SBL) fosters complex skill development but may cause cognitive overload without appropriate instructional support. While GenAI tools provide personalized assistance, their integration into teaching and learning presents pedagogical challenges. Grounded in Self-Determination Theory (SDT), this study investigated the effects of SDT-based teacher support on undergraduates' psychological need satisfaction, engagement, and learning outcomes in a GenAI-assisted simulation-based learning environment. Eighty university students participated in a GenAI-assisted performance management simulation activity and were assigned to conditions with or without teacher support. Our analysis showed that teacher support: (i) significantly enhanced competence and relatedness satisfaction; (ii) significantly increased cognitive, emotional, and agentic engagement; (iii) significantly improved learning performance, problem solving, and critical thinking; and (iv) did not significantly promote autonomy satisfaction, behavioral engagement, or creativity. This study underscores the essential role of teacher support in improving student engagement and higher-order thinking skills in learning contexts incorporating GenAI.
ISSN:0735-6331
1541-4140
DOI:10.1177/07356331261421079