Assessing Assessing Students’ Ethical Concerns in AI-Integrated Online Learning Systems: A Study in Batam City

Abstract

The adoption of Artificial Intelligence (AI) in online education introduces ethical concerns related to accuracy, fairness, and accountability. This study examines students’ ethical concerns of AI-integrated learning systems, focusing on AI-generated materials, attendance monitoring, and chatbot interactions. A mixed-method approach combining qualitative and quantitative techniques was used, involving interviews with 48 students from three different educational levels in Batam City. Thematic analysis identified five dominant themes. These included AI as a useful yet unreliable learning assistant, concerns about fairness in AI-based monitoring, uncertainty regarding responsibility and accountability, the need for transparent institutional policies, and limited AI literacy leading to overreliance. The study reports its findings using percentage-based distributions to illustrate the prevalence of these concerns across educational levels. The results indicate that students’ acceptance of AI in online learning is closely tied to the presence of human oversight, transparent institutional policies, and clearly defined accountability mechanisms. The novelty of this study lies in its focus on a pre-adoption educational environment, where AI is not yet fully institutionalized. Unlike prior studies examining post-implementation contexts, this research captures students’ anticipatory ethical expectations, highlighting concerns often overlooked in retrospective evaluations. The study contributes by providing empirical evidence across educational levels, offering localized insights from a developing Indonesian city, and extending AI ethics research beyond technology-advanced settings. The findings emphasize the importance of human oversight, accountability mechanisms, and transparent institutional policies for ethically grounded AI governance in education.