Preprint
A Dialogic Approach to Transform Teaching, Learning & Assessment with Generative AI in Secondary Education
Social Science Research Network : SSRN
The Social Science Research Network (SSRN) and Elsevier Inc.
2024
Abstract
This paper explores the pedagogical potential of Generative Artificial Intelligence (GenAI) in secondary education through a dialogic approach to teaching, learning and assessment. It presents an ongoing action research project in collaboration with a high school in Western Australia, involving four teachers to integrate GenAI in their classrooms. The study aims to develop and evaluate innovative pedagogies for leveraging GenAI to enhance educational practices and student learning outcomes across three action research teams focusing on critical questioning, assessment and differentiation. Drawing on Bakhtin's concept of heteroglossia, the study conceptualizes GenAI not as a definitive knowledge provider but as a dialogic agent that facilitates collaborative dialogue and co-construction of knowledge among students. This perspective encourages students to critically engage with AI-generated content and integrate multiple viewpoints into their learning, thus fostering key epistemic skills. Initial findings demonstrate active student engagement in dialogues with GenAI, highlighting the use of follow-up questions that indicate critical thinking and creativity. These findings underscore the significance of integrating multiple perspectives and fostering epistemic skills among students, promoting a comprehensive and ethical approach to AI use in education. The research calls for further exploration of GenAI's pedagogic potential and its broader implications for educational practices, suggesting a promising avenue for pedagogical innovation and the development of critical thinking skills in the digital age.
Details
- Title
- A Dialogic Approach to Transform Teaching, Learning & Assessment with Generative AI in Secondary Education
- Authors/Creators
- Kok-Sing TangGrant CooperNatasha RappaMartin CooperCraig SimsKaren Nonis
- Publication Details
- Social Science Research Network : SSRN
- Publisher
- The Social Science Research Network (SSRN) and Elsevier Inc.; Perth, WA, Australia
- Identifiers
- 991005649770107891
- Copyright
- Copyright © 2024 Elsevier Inc.
- Murdoch Affiliation
- School of Education
- Language
- English
- Resource Type
- Preprint
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