From Data to Decisions: Leveraging AI for Proactive Education Strategies

Abstract

The advancement of Artificial Intelligence (AI) and Large Language Models (LLMs) ushers in a new era in education, characterized by more adaptive, personalized learning experiences. This literature review examines the profound impact of these technologies on student engagement, achievement, and personalized learning within higher education institutions. Through a systematic analysis of scholarly articles from 2022 to 2024, this review explores how AI is reshaping educational practices through enhanced feedback mechanisms, predictive analytics, and innovative teaching methodologies. The findings indicate that AI significantly improves student support services by enabling early identification of at-risk students and by facilitating tailored educational interventions. Moreover, the deployment of chatbots and LLMs, such as GPT (generative pre-trained transformer) and BERT (bidirectional encoder representations from transformers), offers promising enhancements in instructional strategies and student assessments, fostering richer, interactive learning environments. However, the integration of these technologies also introduces ethical challenges, necessitating consideration of issues such as data privacy and bias. The review emphasizes the need for ethical frameworks and responsible AI usage to ensure technology enhances educational outcomes without compromising fairness or integrity. Future research directions are suggested, focusing on broader AI applications across various educational settings and the need for longitudinal studies to assess the long-term effects of AI integration in education.