Enhancing pre-service teachers’ understanding of pedagogical key ideas by integrating ChatGPT in ODL course tutorials

Chew, Cheng Meng and Tan, Saw Fen and Ping, Por Fei and Leong, Alexander Funk Yun (2025) Enhancing pre-service teachers’ understanding of pedagogical key ideas by integrating ChatGPT in ODL course tutorials. International Journal of Academic Research in Progressive Education and Development, 14. pp. 287-300. ISSN 2226-6348

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Abstract

This study aimed to enhance pre-service teachers’ understanding of pedagogical key ideas by integrating ChatGPT in the open and distance learning (ODL) pedagogy course tutorials. Purposive sampling was employed in this case study to select nine pre-service teachers from an ODL university. Data were collected through the participants’ reflective reports, video recordings of their presentation of reflective reports, and revised reflective reports. Descriptive statistics and Friedman test with post hoc Wilcoxon signed rank tests were used to analyze the data. The findings showed that 55.56% of the participants achieved a substantial understanding of pedagogical key ideas in their initial reflective reports and their presentation of reflective reports, respectively, while 44.45% achieved a partial understanding. The participants improved in their revised reflective reports after incorporating feedback from the tutor and peers, with 55.56% achieved a high understanding of pedagogical key ideas, 33.33% achieved a substantial understanding, while 11.10% achieved a partial understanding. The Friedman test with post hoc Wilcoxon signed rank tests showed that there was a significant difference in the participants’ understanding of pedagogical key ideas before and after, and during and after the tutorials.

Item Type:	Article
Keyword:	Teacher Education, Pedagogy, Chatgpt, Pre-Service Teachers, Open and Distance Learning
Subjects:	L Education > LB Theory and practice of education > LB5-3640 Theory and practice of education > LB1025-1050.75 Teaching (Principles and practice) Q Science > QA Mathematics > QA1-939 Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software
Department:	FACULTY > Faculty of Education and Sport Studies
Depositing User:	SITI AZIZAH BINTI IDRIS -
Date Deposited:	26 Aug 2025 14:13
Last Modified:	26 Aug 2025 14:13
URI:	https://eprints.ums.edu.my/id/eprint/45054

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