Artificial Intelligence Interaction in Higher Education: A Life-Course Perspective on Digital Well-Being, Learning Outcomes, Motivation,  and Ethical Awareness

Ikrananda; Indah Amaliah; Annajmi Rauf; Muh. Yusril Anam; Irwansyah Suwahyu

doi:10.66053/aillce.v1i1.2

Authors

Ikrananda Universitas Negeri Makassar
Indah Amaliah Universitas Negeri Makassar
Annajmi Rauf Universitas Negeri Makassar
Muh. Yusril Anam Necmettin Erbakan University
Irwansyah Suwahyu Universitas Islam Negeri Sunan Kalijaga Yogyakarta

DOI:

https://doi.org/10.66053/aillce.v1i1.2

Keywords:

Digital Well-Being, Instructional Design Quality, Artificial intelligence in education, Life-course education, Learning motivation

Abstract

Purpose – The increasing integration of artificial intelligence (AI) in higher education offers significant opportunities to enhance learning effectiveness, yet it also raises concerns related to digital well-being, learner motivation, and ethical awareness. From a life-course education perspective, early adulthood represents a critical transitional phase in which patterns of interaction with AI may shape long-term learning habits and readiness for lifelong learning. However, empirical evidence examining how AI interaction influences learning outcomes through psychological and instructional mechanisms remains limited. This study examines the effects of student interaction with AI on learning outcomes, learning motivation, and ethical awareness, with digital well-being and instructional design quality positioned as mediating variables.
Design/methods/approach – A quantitative cross-sectional survey was conducted with 145 undergraduate students at a public university in Indonesia. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine direct and mediating relationships among the proposed constructs.
Findings – The results indicate that student interaction with AI has a significant positive effect on digital well-being, instructional design quality, learning motivation, and learning outcomes. Digital well-being and instructional design quality serve as important mediating mechanisms through which AI interaction enhances motivation and academic achievement. However, interaction with AI does not directly improve students’ ethical awareness, suggesting that ethical sensitivity does not emerge automatically through AI use without explicit pedagogical intervention.
Research implications/limitations – These findings underscore the importance of designing AI-supported learning environments that promote cognitive engagement, digital well-being, and pedagogical quality while deliberately integrating ethical instruction. The study is limited by its cross-sectional design, single-institution context, and reliance on self-reported data.
Originality/value – This study contributes to the literature on artificial intelligence in education by integrating digital well-being and instructional design quality as mediating mechanisms within a life-course framework, offering insights into how AI interaction during early adulthood may influence sustainable and responsible lifelong learning.

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