{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T07:14:23Z","timestamp":1778224463874,"version":"3.51.4"},"reference-count":82,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Hong Kong Research Grants Council, University Grants Committee","award":["17605221"],"award-info":[{"award-number":["17605221"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Learning Technol."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tlt.2025.3567995","type":"journal-article","created":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T17:53:51Z","timestamp":1746640431000},"page":"542-555","source":"Crossref","is-referenced-by-count":4,"title":["Parameter-Efficiently Fine-Tuning Large Language Models for Classroom Dialogue Analysis"],"prefix":"10.1109","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-6488-0234","authenticated-orcid":false,"given":"Deliang","family":"Wang","sequence":"first","affiliation":[{"name":"Faculty of Education, The University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9807-3623","authenticated-orcid":false,"given":"Yaqian","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Educational Technology, Beijing Normal University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9753-1845","authenticated-orcid":false,"given":"Jinjiang","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, The University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6847-4013","authenticated-orcid":false,"given":"Gaowei","family":"Chen","sequence":"additional","affiliation":[{"name":"Faculty of Education, The University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1080\/0305764X.2013.786024"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.lcsi.2023.100702"},{"key":"ref3","volume-title":"The Dialogic Imagination: Four Essays","author":"Bakhtin","year":"2010"},{"key":"ref4","volume-title":"Mind in Society: The Development of Higher Psychological Processes","volume":"86","author":"Vygotsky","year":"1978"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.edurev.2024.100638"},{"key":"ref6","volume-title":"Socializing Intelligence Through Academic Talk and Dialogue","author":"Asterhan","year":"2015"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.lcsi.2019.02.003"},{"key":"ref8","article-title":"How (well structured) talk builds the mind","volume":"163","author":"Resnick","year":"2010","journal-title":"Innovations Educ. Psychol.: Perspectives Learn., Teach. Hum. Develop."},{"key":"ref9","volume-title":"Towards Dialogic Teaching: Rethinking Classroom Talk","author":"Alexander","year":"2008"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.tsc.2011.08.002"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s11217-007-9071-1"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.lcsi.2020.100404"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijer.2023.102275"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.acl-srw.9"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1177\/0735633120968554"},{"key":"ref16","first-page":"515","article-title":"Can chatGPT detect student talk moves in classroom discourse? a preliminary comparison with bert","volume-title":"Proc. 16th Int. Conf. Educ. Data Mining","author":"Wang","year":"2023"},{"issue":"2","key":"ref17","first-page":"304","article-title":"Multi-dimensional performance analysis of large language models for classroom discussion assessment","volume":"16","author":"Tran","year":"2024","journal-title":"J. Educ. Data Mining"},{"key":"ref18","first-page":"7671","article-title":"Enhancing talk moves analysis in mathematics tutoring through classroom teaching discourse","volume-title":"Proc. 31st Int. Conf. Comput. Linguistics","author":"Cao","year":"2025"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.caeai.2022.100074"},{"key":"ref20","first-page":"27730","article-title":"Training language models to follow instructions with human feedback","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Ouyang","year":"2022"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s10639-023-12146-0"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.bea-1.53"},{"key":"ref23","article-title":"Parameter-efficient fine-tuning for large models: A comprehensive survey","author":"Han","year":"2024"},{"key":"ref24","article-title":"Growth through English, a report based on the Dartmouth seminar 1966","author":"Dixon","year":"1967"},{"key":"ref25","first-page":"79","article-title":"Talking to learn","volume-title":"Proc. Lang., Learner, Sch.","author":"Britton","year":"1969"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"146","DOI":"10.4135\/9781452226552.n6","article-title":"Talking to learn","volume-title":"Proc. Handbook Narrative Inquiry: Mapping Methodol.","author":"Hollingsworth","year":"2007"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.4135\/9781473955011.n4"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1017\/9781108888295.026"},{"key":"ref29","volume-title":"Culture and Pedagogy","author":"Alexander","year":"2000"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.sbspro.2015.09.101"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1177\/0033688216631171"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1080\/02671522.2018.1481140"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3102\/978-0-935302-43-1_27"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1207\/s15327809jls1503_3"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.tate.2022.103631"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1080\/09500782.2024.2343292"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2024.101105"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1348\/000709909X479853"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.4337\/9781035321544.00018"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s10956-024-10154-4"},{"key":"ref41","volume-title":"Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists","author":"Zheng","year":"2018"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3027385.3027417"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3506860.3506896"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-07221-0_28"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/2930238.2930250"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2761740"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3106324"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1111\/bjet.13156"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.130"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-78292-4_30"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1111\/bjet.13466"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TLT.2024.3403135"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1038\/s41539-024-00273-3"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.caeai.2024.100325"},{"key":"ref55","article-title":"Comparative analysis of GPT-4 and human graders in evaluating praise given to students in synthetic dialogues","author":"Hirunyasiri","year":"2023"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICALT58122.2023.00100"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/s40593-024-00408-y"},{"key":"ref58","article-title":"A survey of large language models","author":"Zhao","year":"2023"},{"key":"ref59","article-title":"Large language models: A survey","author":"Minaee","year":"2024"},{"key":"ref60","article-title":"Emergent abilities of large language models","volume":"2022","author":"Wei","year":"2022","journal-title":"Trans. Mach. Learn. Res."},{"key":"ref61","article-title":"Instruction tuning for large language models: A survey","author":"Zhang","year":"2023"},{"key":"ref62","article-title":"Fine-tuning can distort pretrained features and underperform out-of-distribution","volume-title":"Proc. 10th Int. Conf. Learn. Representations","author":"Kumar","year":"2022"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-025-11236-4"},{"key":"ref64","article-title":"Parameter-efficient fine-tuning methods for pretrained language models: A critical review and assessment","author":"Xu","year":"2023"},{"key":"ref65","article-title":"Bloom: A 176b-parameter open-access multilingual language model","author":"Scao","year":"2023"},{"key":"ref66","article-title":"Speciality vs generality: An empirical study on catastrophic forgetting in fine-tuning foundation models","author":"Lin","year":"2023"},{"key":"ref67","first-page":"2790","article-title":"Parameter-efficient transfer learning for NLP","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Houlsby","year":"2019"},{"key":"ref68","article-title":"LoRA: Low-rank adaptation of large language models","volume-title":"Proc. 10th Int. Conf. Learn. Representations","author":"Hu","year":"2022"},{"key":"ref69","first-page":"4654","article-title":"The talkmoves dataset: K-12 mathematics lesson transcripts annotated for teacher and student discursive moves","volume-title":"Proc. 13th Lang. Resour. Eval. Conf.","author":"Suresh","year":"2022"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijer.2017.11.003"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-55560-2_5"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1145\/3560815"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1145\/3657604.3664664"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.568"},{"key":"ref75","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","volume-title":"Proc. NAACL-HLT","author":"Devlin","year":"2019"},{"key":"ref76","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","volume":"364","author":"Liu","year":"2019"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.bea-1.11"},{"key":"ref78","first-page":"22199","article-title":"Large language models are zero-shot reasoners","volume-title":"Proc. 36th Int. Conf. Neural Inf. Process. Syst.","author":"Kojima","year":"2022"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1007\/s00146-020-01054-3"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.4324\/9781410617071"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1007\/s11423-023-10338-6"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2019.103670"}],"container-title":["IEEE Transactions on Learning Technologies"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/4620076\/10810756\/10992249.pdf?arnumber=10992249","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T18:00:58Z","timestamp":1748282458000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10992249\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":82,"URL":"https:\/\/doi.org\/10.1109\/tlt.2025.3567995","relation":{},"ISSN":["1939-1382","2372-0050"],"issn-type":[{"value":"1939-1382","type":"electronic"},{"value":"2372-0050","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}