A Multi-Paradigmatic Perspective Towards the Adoption of Artificial Intelligence in Education

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Abstract

This paper presents a multi-paradigmatic perspective for evaluating artificial intelligence (AI) tools through the lens of established (i.e., Behaviorism, Constructivism, Social Constructivism) and emerging (i.e., Complexity Theory) learning theories. We synthesized and modified current instructional design principles with contemporary AI applications in alignment with learning theories and pedagogy. We developed a set of guiding questions that can enable educators to critically evaluate the pedagogical needs of their students, and make informed decisions about AI integration in their teaching practice. This work contributes to the growing discourse on educational technology by offering a theoretically-grounded approach to evaluating AI tools' educational value and their appropriateness for inclusive learning environments.

Authors

• Haidee A. Jackson, University of Texas - Permian Basin

• Suman Rath, Montclair State University