Exploring the Digital Competence of Language Teachers in ChatGPT Integration in Higher Education: A Systematic Review (78314)

Session Information: Teaching Experiences, Pedagogy, Practice & Praxis
Session Chair: Pei-I Chou

Wednesday, 27 March 2024 10:05
Session: Session 1
Room: Room 708
Presentation Type: Oral Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

The emergence of novel large language models represented by ChatGPT sparked concerns among language teachers regarding their professional roles and perceived barriers to integrating Artificial Intelligence in Education (AlEd). However, there are fewer systematic reviews that specifically investigate the digital competence of language teachers in applying ChatGPT to language teaching and learning. This research aims to address the gap and enlighten stakeholders like policymakers, technology experts, and researchers to work together on effective ChatGPT integration.
By conducting a systematic review of 18 articles published in journals and conferences between December 2022 and November 2023, this study deploys Ng et al.'s (2023) instructional design framework for AI literacy education to sort out articles following four dimensions: 1) teachers' professional engagement; 2) instructional support; 3) content choices across disciplines; and 4) students' learning competencies.
Results indicate that: 1) Language teachers exhibit a positive attitude towards perceived usefulness yet lack a clear AI basic in their engagement; 2) Instructors encounter technological challenges in optimizing contextualized designs and learning assessment; 3) Teachers focus more on students’ social-emotional wellbeing when balancing students’ high-level cognitive skills in chosen contents; 4) Teachers are worried about issues about students' over-dependency on ChatGPT and plagiarism, alongside language skill acquisition. In summary, language teachers are not digitally AI-competent in their instruction, although ChatGPT could not replace teachers ‘roles at its nascent stage. Future research should highlight effective strategies to improve instructors' related technical and non-technical competencies and further assess students’ learning outcomes in their self-directed learning contexts.

Fangyan Chen, Lingnan University, China
Jiayi Chen, Lingnan University, China
Zheng Lin, Lingnan University, China

About the Presenter(s)
Ms. Jiayi Chen is currently a doctoral student in the social policy program at Lingnan University, Hong Kong.

Fangyan Chen is a doctoral student and research assistant at the School of Graduate Studies,Lingnan University. Her research interest now focuses on the inter-cultural communication competence of university teachers in the AI-empowered era.

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Posted by Clive Staples Lewis

Last updated: 2023-02-23 23:45:00