Ravi, M. orcid.org/0000-0001-7659-9492 (2025) Using the TPACK Framework for Gen-AI Enabled Learning Activities: Design, Delivery and Evaluation. Journal of Engineering Education Transformations, 38 (IS2). pp. 175-181. ISSN 2349-2473
Abstract
This paper explores the integration of Generative Artificial Intelligence (GenAI) tools in engineering education through the Technological Pedagogical Content Knowledge (TPACK) framework. By designing and implementing AI-enabled learning activities, the study demonstrates how GenAI can enhance student engagement, critical thinking, and overall learning outcomes in the modern classroom. The research was conducted in the context of a two-week intensive course on engineering solutions for a sustainable world, where activities such as AI chatbot discussions, AI-based image generation and AI-designed quizzes were employed. Student feedback on all activities indicated high levels of engagement and improved understanding. The findings suggest that AI tools can make learning more interactive and enjoyable, streamline teaching and assessment processes, while allowing the educator to foster critical thinking and reflective abilities in students. Recommendations for broader implementation center around considerate design of AI-enabled learning activities that align with learning outcomes and requiring students to critically evaluate AI-generated outputs. Thereby, this work serves as a case study for integrating AI in a pedagogically sound manner, offering valuable insights for educators aiming to leverage AI to enhance the student learning experience.
Metadata
Item Type: | Article |
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Authors/Creators: | |
Keywords: | Generative Artificial Intelligence; Learning activities; Student engagement; TPACK framework |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Jul 2025 15:36 |
Last Modified: | 02 Jul 2025 15:36 |
Status: | Published |
Publisher: | Rajarambapu Institute of Technology |
Identification Number: | 10.16920/jeet/2025/v38is2/25021 |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:228498 |