A Segue From Search to Dialogue: Leveraging GenAI for Pre-Service Teacher Training

Marcella Dillig, Anselm Böhmer, Jon Mason, Stephen Bolaji, Illie Isso, Mirona Stănescu, Hilal Sahin, Aslihan Kuraner

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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Abstract

For over two decades, educational technologies have been embedded within an approach to inquiry dominated by the “search paradigm.” However, conversational AI presents an opportunity to shift this paradigm towards enhancing learning through dialogue. This study explores ChatGPT's potential in developing pre-service teachers' interaction skills and competencies, focusing on interculturality. Using participatory action research, the key inquiry is: In what ways can GenAI applications such as ChatGPT serve as dialogue partners to train future educators' (intercultural) interaction skills and competencies? The research covers prompt specification, students' experiences with dialogic learning using ChatGPT, and prospects for using LLMs as dialogue partners in pre-service teachers' training. Qualitative analysis shows ChatGPT can stimulate the learning process, especially when perceived as realistic and challenging. These findings suggest new implementations of LLMs in pre-service teacher education and further research into their potential for enhancing dialogue-based skill development.
Original languageEnglish
Title of host publicationTransforming Education With Generative AI
Subtitle of host publicationPrompt Engineering and Synthetic Content Creation
EditorsRamesh Sharma, Aras Bozkurt
Place of PublicationUnited States
PublisherIGI Global
Chapter2
Pages22-55
Number of pages34
Volume1
Edition1
ISBN (Print)979-8369313510
DOIs
Publication statusPublished - 14 Feb 2024

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