arXiv:2605.29041v1 Announce Type: new Abstract: This study reports findings from a cross-sectional survey (n = 72) of higher education practitioners examining beliefs, behaviors, and institutional conditions related to artificial intelligence (AI) integration in teaching and learning. Grounded in the DOT Framework, which integrates design thinking and open systems theory, the study investigates AI familiarity, usage patterns, design-oriented practices, and pedagogical beliefs. Exploratory factor analysis of 19 belief items identified a three-factor structure: AI Functional Capabilities, Oversi
The proliferation of accessible AI tools necessitates an understanding of practitioner integration and pedagogical beliefs within educational institutions.
Understanding how educators perceive and utilize AI is crucial for effective policy, tool development, and overall integration into the education system, impacting future workforce readiness.
This research provides empirical data on the current state of AI adoption beliefs and behaviors in higher education, shifting discussions from theoretical potential to practical implementation challenges.
- · AI-education platform developers
- · Educational institutions adapting swiftly
- · Students engaging with AI-enhanced learning
- · Traditional education models
- · Educators resistant to AI integration
- · Institutions slow to adopt AI strategies
Increased demand for AI literacy training and support for educators will follow.
Curriculum reforms will likely accelerate to incorporate AI tools and skills development more formally.
The definition of 'teaching' and 'learning' in higher education could fundamentally evolve with deeper AI integration.
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Read at arXiv cs.AI