Document Type

Article

Publication Date

Spring 3-1-2026

Persistent Identifier

http://hdl.handle.net/10950/5150

Abstract

Artificial Intelligence (AI) technologies are increasingly embedded in graduate academic work, shaping how faculty and students perform cognitive, analytical, and knowledge-based tasks. As AI tools become integrated into writing, research, and instructional activities, human–AI interaction has emerged as a central feature of contemporary academic work environments. However, existing research has largely focused on AI adoption and technological capability, with limited attention given to how ongoing human–AI interaction influences well-being experiences in academic contexts. Drawing on the Job Demands-Resources (JD-R) framework, this conceptual paper develops a model that links human–AI interaction to student learning satisfaction, faculty job satisfaction, and emotional exhaustion. This paper advances propositions and outlines directions for future empirical research in graduate academic settings.

Comments

This article is published in the International Journal on Integrating Technology in Education under a Creative Commons Attribution 4.0 International License (CC BY-NC 4.0) which permits unrestricted use, distribution, and reproduction in any medium for non-commercial use provided the original author and source are credited. Copyright © 2026 The Author(s):

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