Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/121745
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dc.contributorDepartment of Electrical and Electronic Engineering-
dc.contributorEducational Development Centre-
dc.creatorChan, CH-
dc.creatorChan, C-
dc.creatorChen, J-
dc.creatorLai, P-
dc.date.accessioned2026-10-09T08:03:19Z-
dc.date.available2026-10-09T08:03:19Z-
dc.identifier.urihttp://hdl.handle.net/10397/121745-
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.subjectAIen_US
dc.subjectEnglish oral presentationsen_US
dc.subjectHybrid intelligenceen_US
dc.subjectPedagogyen_US
dc.subjectPeer assessmenten_US
dc.subjectSelf-assessmenten_US
dc.titleTransforming pedagogy with AI tools : impacts, challenges, and opportunities in higher educationen_US
dc.typeConference Paperen_US
dc.identifier.spage39-
dc.identifier.epage47-
dcterms.abstractTraditional pedagogy positions teachers as the primary source of knowledge, with educators providing academic guidance on English oral presentations—including both content and paralinguistic features—across university disciplines. However, subject-matter instructors often lack expertise in English language delivery, while large class sizes prevent the provision of timely individual feedback. Advances in technology enable a pedagogical shift to fill this gap. Rather than waiting for teacher feedback, students can leverage AI for immediate learning support. However, AI has limitations regarding nuanced aspects of performance. To complement AI feedback, we implemented NinjOrAItor—an AI platform for English oral presentations featuring hybrid intelligence that combines self- and peer-assessment. This hybrid intelligence pedagogy integrates AI capabilities with human insight. The platform addresses key challenges: teacher expertise limitations, scalability issues in large classes, and the need for timely feedback. By integrating AI assessment with structured human intelligence, NinjOrAItor demonstrated improved student presentation performance while maintaining pedagogical quality.-
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. 39-47. 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-n02en_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis research was supported by the TDG Inter-institutional Collaborative Activities (IICA) 2022–25 grant through a partnership between The Hong Kong Polytechnic University (PolyU) and City University of Hong Kong (CityUHK). The authors extend their gratitude to the English instructors at CityUHK and the technical development team at PolyU, whose collaborative efforts have been instrumental in advancing this study on hybrid intelligence in English language education.en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryPublisher permissionen_US
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