Using Curriculum Theory to Inform Approaches to Generative AI in Schools
It addresses the problem of integrating Generative AI into school curricula for educators, but it is incremental as it builds on existing curriculum theories without proposing new methods or data.
This essay examines the pedagogical changes needed in secondary education due to the rise of Large Language Models, using curriculum theory frameworks to analyze challenges like AI reliability and ethical issues, and concludes with a roadmap for future research on AI's impact on education.
In an educational landscape dramatically altered by the swift proliferation of Large Language Models, this essay interrogates the urgent this essay interrogates the urgent pedagogical modifications required in secondary schooling. Anchored in Madeline Grumet's triadic framework of curriculum inquiry, the study delineates the multifaceted relationship between Generative AI and Elliot Eisner's explicit, implicit, and null curriculum concepts. It scrutinizes the logistical and ethical challenges, such as the reliability of AI detectors, that educators confront when attempting to assimilate this nascent technology into long-standing curricular structures. Engaging with Ted Aoki's theory of the "zone of between", the essay illuminates educators' dilemmas in reconciling prescriptive curricular aims with the fluid realities of classroom life, all within an educational milieu in constant flux due to Generative AI. The paper culminates in a reflective analysis by the researcher, identifying avenues for further scholarly investigation within each of Grumet's constitutive strands of curriculum theory, thereby providing a roadmap for future research on Generative AI's transformative impact on educational practice.