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Artificial Intelligence Enabled Model for Cultivating Interdisciplinary Innovation Competence in Higher Education

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  • Gao, Min

Abstract

The rapid development of artificial intelligence is driving the transformation of higher education paradigms toward intelligence, integration, and innovation. As a core indicator for cultivating interdisciplinary talents, interdisciplinary innovation competence requires the establishment of an educational model that aligns with the learning characteristics and competency demands of the AI era. Based on innovation competence development theory, interdisciplinary integration theory, and educational digital transformation theory, this study proposes a pathway mechanism for AI-empowered interdisciplinary innovation competence cultivation in higher education. Accordingly, an AI enabled interdisciplinary innovation competence cultivation model with "discipline-oriented, innovation practice, and outcome evaluation" is constructed. The results indicate that this model enables AI to significantly enhance students' interdisciplinary design thinking, complex problem-solving ability, and quality of innovative expression, while improving learning initiative and collaboration depth, boosting teaching efficiency, and facilitating the formation of a multi-agent collaborative teaching and learning mechanism among humans and machines. The research provides theoretical support and practical reference for the reconstruction of innovation-oriented interdisciplinary talent cultivation models and intelligent teaching reform in higher education.

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  • Gao, Min, 2025. "Artificial Intelligence Enabled Model for Cultivating Interdisciplinary Innovation Competence in Higher Education," European Journal of Education Science, Pinnacle Academic Press, vol. 1(3), pages 32-38.
    • Handle: RePEc:dba:ejesaa:v:1:y:2025:i:3:p:32-38
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