GenAI and Effective Reading Among University Students: Prospects, Challenges, and Future Directions

Abstract

The rapid development of Generative Artificial Intelligence (GenAI) has significantly influenced university students' reading habits, with both positive and negative implications. While there have been increased use of GenAI among university students, some scholars relate its use with negative impacts regarding students reading habits while others relate it with positive. It is against this backdrop that the present study was carried out to explore prospects, challenges and future directions of GenAI in the developing effective reading amongst university students. The study employed systematic review of literature. Findings revealed that GenAI presents both prospects and challenges for students’ effective reading. Prospects include improved accessibility, convenience of reading, personalized reading resources and interactive reading. Regarding challenges, the study found that GenAI can potentially create students’ overdependency on it. In addition, there are potential biasness and inaccuracies of AI algorithms that can lead to a generation of biased reading contents. The system can also lead to breach of data privacy and it is resources intensive. Although the study established both prospects and challenges of GenAI in enhancing reading, most of the challenges are manageable. Provided that appropriate measures are implemented it can be reasonably concluded that the prospects outweigh its challenges. It was, further, found that future directions of AI in developing reading environments involve integration of AI with virtual reality, diminished human-human interaction, human-AI integration, and lifelong learning. The study calls for universities to institute and operationalize students’ data governance and protection policies, among other recommendations.