Practitioner Beliefs and Behaviors in AI-Enhanced Education: DOT Framework Survey Evidence

2026-05-27

AI Summary

This study investigates higher education instructors’ beliefs, practices, and institutional barriers concerning the integration of artificial intelligence (AI) into teaching, revealing a gap between their approaches and design-oriented theory. Grounded in the Design-Oriented Technology (DOT) framework, the research provides the first empirical validation of DOT through a cross-sectional survey of 72 educators. It proposes a three-dimensional belief structure encompassing AI functionality awareness, oversight governance, and teacher collaboration. Employing exploratory factor analysis on 19 belief items and integrating design thinking with open systems theory, the study finds that while instructors generally recognize AI’s pedagogical value, their implementation lacks systematic needs assessment and feedback mechanisms. Moreover, institutional constraints—including absent policy guidance, insufficient training, and inadequate infrastructure—significantly impede effective AI adoption in educational practice.

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, Oversight and Governance, and Instructor Collaboration and Planning (α = .90). Results indicate that practitioners hold favorable views of AI as a pedagogical support while maintaining strong commitments to human oversight and critical evaluation. Reported practices emphasize iterative prompting and content generation, with less consistent use of needs assessment and feedback loops. Institutional barriers including limited policy, training, and infrastructure were widely reported. These findings provide preliminary empirical support for the DOT Framework as a descriptive model of practitioner beliefs and practices, while also highlighting gaps between design-oriented theory and current implementation. The study contributes an initial measurement structure and identifies directions for confirmatory validation and outcome-based research linking AI-supported design practices to instructional quality.

Problem

• AI-enhanced education
• practitioner beliefs
• instructional design
• institutional barriers
• pedagogical practices

Innovation

• DOT Framework
• design thinking
• AI-enhanced education
• exploratory factor analysis
• practitioner beliefs