Date
12-4-2025
Department
School of Education
Degree
Doctor of Philosophy in Education (PhD)
Chair
Vonda S. Beavers
Keywords
Artificial Intelligence, rural education, teacher workload, teacher well-being, educational technology, phenomenological study, JD-R model, teacher job satisfaction, instructional technology, qualitative research
Disciplines
Education | Educational Methods
Recommended Citation
Morris, Courtnee R., "How Rural Public Middle School Teachers Describe the Influence of Artificial Intelligence Integration on Their Workload Management: A Qualitative Phenomenological Study" (2025). Doctoral Dissertations and Projects. 7679.
https://digitalcommons.liberty.edu/doctoral/7679
Abstract
The purpose of this phenomenological study is to explore the work processes of public middle school teachers in rural areas of Northwest Ohio regarding the integration of Artificial Intelligence into their professional practice. Work processes were defined as teachers’ perceptions, interactions, and reflections on how AI influenced their workload, instructional practices, and job satisfaction. The Job Demands-Resources model provided the theoretical framework, offering a lens to examine how AI tools functioned as both resources and demands in the teaching environment. This framework helped illuminate the interaction between technology use and educator well-being in rural educational settings. The central research question guiding this study asked: How do rural public middle school teachers describe the influence of AI integration on their workload management? Participants were recruited using purposive and snowball sampling from rural middle schools in Northwest Ohio. Data were collected through individual interviews, focus groups, and document analysis, then analyzed thematically. Key findings indicated that AI served as both a workload-reducing resource and a spark for instructional innovation, enabling teachers to regain time, brainstorm creative approaches, and design new types of learning experiences. At the same time, participants raised concerns about student overreliance, loss of authentic voice, and inequities in access to professional development and infrastructure. The study contributes to the literature by extending the JD-R model to account for AI’s dual role as a resource and a potential demand, while also highlighting rural-specific inequities. These insights suggest that AI integration holds promise for supporting teacher well-being and instructional quality, but its success depends on ethical use, systemic support, and equitable access.
