Navigating Artificial Intelligence in Higher Education: Students’ Social Learning Experiences, Ethical Concerns, and Academic Adaptation - Sarifudin Sarifudin; Rifki Ayu Rosmita (Gema Cendekia Institute, 2026)
The rapid advancement of Generative Artificial Intelligence (GAI) has triggered significant transformations in higher education by reshaping how students learn, interact, and construct knowledge. This article examines the dynamics of students’ social learning experiences, identifies the ethical challenges associated with the use of generative AI, and explores the forms of academic adaptation emerging within contemporary higher education environments. Employing a systematic literature review approach, the study analyzes 30 key sources, including peer-reviewed journal articles, academic books, and international policy documents addressing AI in higher education. Thematic analysis revealed three major themes: the transformation of social learning practices, ethical dilemmas surrounding AI use, and students’ academic adaptation strategies. The findings suggest that generative AI functions as a new mediating agent in social learning, facilitating a shift from knowledge acquisition toward knowledge co-creation. However, this transformation also raises concerns regarding academic integrity, cognitive dependency, algorithmic bias, and data privacy. In response, students and institutions are developing adaptive strategies through AI literacy initiatives, authentic assessment practices, and human–AI collaborative learning models. This article proposes the Human–AI Academic Adaptation Framework as a conceptual model for understanding the interrelationships among social learning, ethics, and academic adaptation in the age of artificial intelligence.