Peran Artificial Intelligence dalam transformasi pembelajaran di perguruan tinggi

Tren, tantangan, dan implikasi masa depan

Abstract

The integration of Artificial Intelligence (AI) into the higher education ecosystem has triggered a fundamental paradigm shift from a "one-size-fits-all" model to highly personalized adaptive learning. This study aims to critically analyze AI adoption trends, identify emerging ethical and technical barriers, and project long-term implications for the academic landscape and future labor market. Using a Systematic Literature Review (SLR) method within the PRISMA framework, this research synthesizes data from 50 selected articles to perform a comprehensive analysis of the effectiveness of technologies such as Large Language Models (LLM), Intelligent Tutoring Systems (ITS), and Predictive Analytics. The analysis shows that AI integration can improve administrative efficiency by up to 40% and student engagement by 35% through precise real-time feedback mechanisms. However, significant multidimensional challenges were found, including the "black box" algorithm phenomenon (algorithmic bias), data privacy risks, and academic integrity crises due to uncontrolled Generative AI usage. These findings indicate that the future of higher education does not depend on total automation, but on a hybrid collaboration model (human-in-the-loop), where AI functions as a cognitive copilot extending human intellectual capacity. This article recommends a new policy framework for ethical, inclusive, and sustainable AI governance on campus.