Abstract: Guided by the Human-Centered AI–Teaching Presence (HC-AI-TP) framework, this study examined whether artificial intelligence (AI) functions as a mixed blessing in higher education by testing its relationships with perceived learning quality and academic effort and by assessing the moderating role of instructor guidance. Using quantitative, nonexperimental correlational design, survey data were collected from 182 undergraduate and graduate students enrolled in higher education courses where AI tools were available. Measures assessed AI use, perceived learning quality, academic effort, and instructor guidance. Data were analyzed using correlation, linear regression, and moderated regression techniques. Results showed that AI use was positively associated with perceived learning quality (β = .21, p = .005, R² = .04) but negatively associated with academic effort (β = −.26, p < .001, R² = .06). Instructor guidance significantly moderated both relationships, strengthening the positive association between AI use and learning quality (β = .19, p = .003, ΔR² = .03) and reducing the negative association between AI use and academic effort (β = .22, p = .001, ΔR² = .04). All four null hypotheses were rejected. These findings demonstrate that AI’s impact on learning is conditional rather than uniform. While AI use may enhance perceived learning quality, it may also reduce academic effort unless guided by clear instructional expectations. The study provides empirical support for HC-AI-TP by showing that teaching presence is the central mechanism through which AI supports meaningful learning while preserving student effort. The results help explain inconsistent findings in prior research and underscore the importance of human-centered instructional guidance in AI-enabled higher education.
Keywords: artificial intelligence, teaching presence, learning quality, academic effort, higher education.
Title: Artificial Intelligence as a “Mixed Blessing” in Online Higher Education: A Human-Centered AI–Teaching Presence (HC-AI-TP) Perspective
Author: Dr. David Augustine Bull
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 14, Issue 1, January 2026 - March 2026
Page No: 88-103
Research Publish Journals
Website: www.researchpublish.com
Published Date: 02-February-2026
