Exploring the impact of generative AI literacy on teaching practices and pedagogical alignment

Gennadii Miroshnikov and Mike Bennett
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Gennadii Miroshnikov: King’s College London, UK
Mike Bennett: King’s College London, UK

Advances in Online Education: A Peer-Reviewed Journal, 2025, vol. 4, issue 1, 6-23

Abstract: The embedding of generative AI (GenAI) tools in education has become a groundbreaking development, creating significant opportunities to enrich teaching practices and drive innovative learning design. This study investigates how educators evaluate the impact of these tools on their teaching, the extent to which their practices align with established pedagogical frameworks and how artificial intelligence (AI) literacy influences their adoption and use of such technologies. Employing a mixed-methods approach, the research analysed survey data from participants of a Generative AI in Education massive online open courses (MOOC). Quantitative findings reveal high levels of satisfaction with AI tools, with educators reporting improved engagement and efficiency. Qualitative insights highlight key benefits, such as support for higher-order thinking and personalised learning, alongside challenges related to time constraints, AI literacy gaps and resource limitations. This study employs theoretical frameworks, including Technological Pedagogical Content Knowledge (TPACK), Substitution, Augmentation, Modification and Redefinition (SAMR) and Bloom’s Taxonomy, to evaluate how educators integrate AI into their teaching. While many respondents reported achieving a balance between traditional and innovative pedagogies, fewer utilised AI tools for transformative practices. The findings underscore the need for targeted professional development, tailored resources and ongoing ethical considerations to maximise the benefits of AI in education. This research advances the discussion on AI-enhanced teaching by offering actionable insights for educators and institutions aiming to align AI tools with pedagogical goals. By addressing barriers and utilising the functionalities of GenAI, this study advocates for its role in redefining teaching and learning, setting the stage for more engaging, efficient and equitable educational experiences. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.

Keywords: generative AI; AI literacy; pedagogical frameworks; TPACK; SAMR; Bloom’s Taxonomy; mixed-methods research (search for similar items in EconPapers)
JEL-codes: A2 I2 (search for similar items in EconPapers)
Date: 2025
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