Forschungsprojekt ::

Beyond Technology Acceptance: Trust, Values, and Human Agency in AI-Enhanced Learning

Projektbeschreibung

Models such as TAM and UTAUT have played an important role in explaining educational technology adoption. However, contemporary AI-enhanced systems differ from many earlier digital technologies because they can generate content, recommend actions, personalize learning experiences, and participate in decisions traditionally associated with educators and learners. Consequently, adoption increasingly depends on users’ perceptions of trustworthiness, transparency, control, ethical acceptability, and alignment with educational and human values. Understanding these dimensions requires dialogue between educational technology, pedagogy, human-computer interaction, psychology, ethics, learning sciences, and value-sensitive approaches to technology design.

This Research Topic seeks to advance understanding of these factors and to encourage theoretical and empirical work that extends, revises, or complements established technology-acceptance frameworks. Its goal is to identify the conditions under which AI-enhanced learning technologies are not only adopted, but also perceived as trustworthy, educationally meaningful, compatible with human values, and supportive of learners’ and educators’ agency.

We welcome original research, systematic reviews, conceptual or theoretical papers, and methodological or design-oriented studies addressing topics including:

• extensions of TAM, UTAUT, and related acceptance models for AI-enhanced education
• trust and reliance on educational AI
• human agency, autonomy, and meaningful human control
• transparency, explainability, perceived intelligence, and perceived risk
• value-sensitive and human-centered design of educational AI
• learner and educator attitudes toward generative AI, intelligent tutoring systems, educational agents, recommender systems, and adaptive or personalized learning
• AI literacy, teacher preparedness, and pedagogically responsible adoption
• cultural, educational, and institutional factors shaping acceptance and use
• the relationship between personalization and learner agency

The Topic particularly encourages interdisciplinary and cross-cultural studies that clarify how technological, psychological, pedagogical, and value-related factors interact in shaping human engagement with AI-enhanced learning.