Date
8-29-2025
Department
School of Education
Degree
Doctor of Philosophy in Education (PhD)
Chair
Alex Boggs
Keywords
Instructional Design, AI, Artificial Intelligence, Education, AI Literacy, AI Adoption, UTAUT
Disciplines
Education
Recommended Citation
Malone, Cynthia R., "Generational Divide: Exploring Instructional Designers' Perceptions of Artificial Intelligence in the Instructional Design Process" (2025). Doctoral Dissertations and Projects. 7403.
https://digitalcommons.liberty.edu/doctoral/7403
Abstract
The purpose of this phenomenological study was to understand the lived experiences of instructional designers as they designed courses using AI technology and to understand their perceptions surrounding the integration of AI into the instructional design process. The theory that guided this study was the Unified Theory of Acceptance and Use of Technology (UTAUT), a framework that involves the pillars of performance expectancy, effort expectancy, social influence, and facilitating conditions, which collectively influence one’s intention to adopt a new technology. Varying generational perceptions impacted instructional designers' adoption of AI. The central research question for this study asked, What are the lived experiences of instructional designers as they design a course using AI technology? A hermeneutic-phenomenological research method was used to describe and understand the essence of the lived experiences of instructional designers. The research setting took place in various education and training environments across different industries for adult learners. Participants in this study were instructional designers from online universities, government agencies, contracting companies, freelancers, and entrepreneurial settings. The data collection methods used were in-depth individual interviews, focus groups, and qualitative surveys. Thematic analysis was used to analyze the data and revealed that generational differences in AI adoption were shaped more by institutional context and self-efficacy than age. While AI was valued for efficiency, concerns persisted about its cultural sensitivity and pedagogical accuracy. Barriers such as low AI literacy, limited access, and insufficient professional development were common across generations.
