Learning in the Presence of Machines: A Study of Student Interactions with AI-Based Educational Tools

Abstract

Artificial Intelligence (AI) has become increasingly embedded in educational technology, particularly through AI-based tutoring systems that support autonomous learning in higher education. While the functionality and effectiveness of these systems have been widely studied, less is known about how students subjectively experience and make meaning of their interactions with AI tutors. The present study addresses this gap by asking: how do university students experience AI-based tutoring in self-directed learning environments? Conducted at a public university in Indonesia, this research explores the lived experiences of twelve undergraduate students engaged with AI tutoring systems over a semester. Data were collected through in-depth semi-structured interviews and analyzed using Interpretative Phenomenological Analysis (IPA), revealing four major experiential themes: negotiating autonomy, emotional ambivalence, forming quasi-social connections, and tensions between efficiency and personalization. The results show that students construct complex emotional and cognitive relationships with AI tutors that extend beyond functional use, influencing their motivation, engagement, and perceived support. These findings demonstrate the need to view AI not merely as a technical tool but as a relational agent within the learning experience. By uncovering the essence of learner-AI interaction, this study contributes to a deeper understanding of the human dimensions of digital learning and provides guidance for developing more empathetic, learner-centered AI technologies in education.