TY - CONF
T1 - Interdisciplinary Perspectives on Generative Artificial Intelligence Adoption in Higher Education: A Theoretical Framework Review
AU - Duah, James Ewert
AU - Lu, Xin
AU - McGivern, Paul
AU - Jing, Yanguo
PY - 2025/1/1
Y1 - 2025/1/1
N2 - The ongoing integration of Generative Artificial Intelligence (GenAI) within higher education (HE) signifies a pivotal shift in pedagogical paradigms, demanding comprehensive theoretical and practical considerations. This paper critically examines the multifaceted adoption of GenAI in HE by reviewing interdisciplinary theoretical frameworks from psychology, computer science, and pedagogy. It highlights the insufficiency of traditional technology acceptance models, which predominantly address cognitive and rational decision-making processes, and advocates for the inclusion of emotional and ethical dimensions often overlooked in existing frameworks. By synthesizing research across various disciplines, this review identifies significant gaps and proposes an integrated theoretical model to effectively understand and guide GenAI adoption. The proposed framework emphasizes the need for robust, empirically supported methodologies that accommodate the complex, dynamic nature of GenAI applications. This paper not only contributes to academic discourse by providing a comprehensive review of existing literature but also sets a foundation for future empirical studies aimed at refining GenAI integration strategies in HE, ensuring they are ethically aligned and educationally effective.
AB - The ongoing integration of Generative Artificial Intelligence (GenAI) within higher education (HE) signifies a pivotal shift in pedagogical paradigms, demanding comprehensive theoretical and practical considerations. This paper critically examines the multifaceted adoption of GenAI in HE by reviewing interdisciplinary theoretical frameworks from psychology, computer science, and pedagogy. It highlights the insufficiency of traditional technology acceptance models, which predominantly address cognitive and rational decision-making processes, and advocates for the inclusion of emotional and ethical dimensions often overlooked in existing frameworks. By synthesizing research across various disciplines, this review identifies significant gaps and proposes an integrated theoretical model to effectively understand and guide GenAI adoption. The proposed framework emphasizes the need for robust, empirically supported methodologies that accommodate the complex, dynamic nature of GenAI applications. This paper not only contributes to academic discourse by providing a comprehensive review of existing literature but also sets a foundation for future empirical studies aimed at refining GenAI integration strategies in HE, ensuring they are ethically aligned and educationally effective.
U2 - 10.1145/3704289.3704293
DO - 10.1145/3704289.3704293
M3 - Paper
SP - 1
EP - 9
ER -