Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/121764
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dc.contributorDepartment of Management and Marketing-
dc.creatorQi, C-
dc.creatorLei, Y-
dc.date.accessioned2026-10-09T08:03:44Z-
dc.date.available2026-10-09T08:03:44Z-
dc.identifier.urihttp://hdl.handle.net/10397/121764-
dc.descriptionInternational Conference on GenAI and Pedagogical Innovations (GaPI), Hong Kong, 20-22 May 2026en_US
dc.language.isoenen_US
dc.rightsCopyright © 2026en_US
dc.rightsCopyright of the papers is retained by the authors. No part of this collection may be reproduced by any process without prior written permission of the copyright holders.en_US
dc.rightsPosted with permission of the publisher.en_US
dc.subjectChatGPTen_US
dc.subjectEngagementen_US
dc.subjectFeedbacken_US
dc.subjectIntrinsic motivationen_US
dc.subjectLearning outcomesen_US
dc.titleInfluence of ChatGPT’s feedback on student motivation and learning : the moderating role of trusten_US
dc.typeConference Paperen_US
dc.identifier.spage374-
dc.identifier.epage377-
dcterms.abstractThis study investigates the influence of ChatGPT’s feedback on students’ intrinsic motivation, engagement, and learning outcomes in higher education, with a focus on the moderating effect of trust. Drawing from Self-Determination Theory (SDT) and Self-Regulated Learning (SRL) theory, this study examines how AI-generated feedback affects learners’ cognitive learning status and academic performance. A survey was conducted among 300 programming students; data analysis results revealed that feedback from ChatGPT enhances intrinsic motivation, which leads to a higher level of affective and behavioural engagement, ultimately boosting learning outcomes. However, contrary to our assumption, trust towards ChatGPT negatively (instead of positively) moderates the relationship between feedback and intrinsic motivation. These findings suggest that integrating AI-driven feedback mechanisms like ChatGPT can greatly enhance educational experiences by promoting intrinsic motivation, active engagement, and academic outcomes.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIn Chen, J., Leung, A., Tsang, E., Ng, A., Chau, J., Kam, R., Patel, M., Lo, D., Tam, B., Chon, L., Cheung, K., Tang, E., & Ho, K. (Eds.). Collection of Selected Papers from the International Conference on GenAI and Pedagogical Innovations 2026, p. 374-377. Hong Kong : Educational Development Centre, Hong Kong Polytechnic University, 2026-
dcterms.issued2026-
dc.relation.conferenceInternational Conference on GenAI and Pedagogical Innovations [GaPI]-
dc.description.validate202610 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera4809-n21en_US
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryPublisher permissionen_US
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