GenAI and effective reading among university students: Prospects, challenges, and future directions - George Matto; Jaffar Msafiri Ponera; Valeria Kyumana (IJIE (Indonesian Journal of Informatics Education), 2025)
Continuous advancements in the fields of science and technology have led to the emergence of innovative technologies such as Generative Artificial Intelligence (GenAI). 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 limitations for students’ effective reading. improved accessibility, convenience of reading, personalized reading resources and interactive reading were found to be the potential prospects. Regarding limitations, 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.  Most of the limitations are, however, manageable. Thus, it was reasonably concluded that the prospects outweigh the limitations. 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.