Exploring the Impact of Artificial Intelligence on Academic Information Sourcing Among University Students in Bayelsa State

Abstract

Abstract This study investigates the impact of Artificial Intelligence (AI) on academic information sourcing among university students in Bayelsa State, Nigeria. With technologies that improve research efficiency, customise learning, and expedite academic duties, artificial intelligence (AI) has emerged as a disruptive force in education. However, there are several obstacles to the widespread use of AI at Nigerian colleges, especially in Bayelsa State, because of poor infrastructure, problems with digital literacy, and ethical dilemmas. Twenty students from Niger Delta University, Federal University Otuoke, and Bayelsa Medical University participated in semi-structured interviews as part of the study's qualitative research design. The study intends to investigate how well-informed students are about AI technologies, how they utilise them for academic purposes, what obstacles they face, and how they see the ethical ramifications of using AI. The research aims to explore students' awareness of AI tools, their utilization of these tools for academic purposes, the challenges they encounter, and their perceptions of the ethical implications associated with AI use. The results show that although students in Bayelsa State are using and becoming more aware of artificial intelligence (AI) tools such as Grammarly, Mendeley, and Google Scholar, their comprehension of these tools' features and advantages is still lacking. Difficulties include limited digital infrastructure, slow internet access, and a lack of training on how to use AI tools effectively. Significant ethical concerns also surface, such as possible plagiarism and an excessive dependence on AI-generated content. The study concludes that universities in Bayelsa State must address infrastructure deficiencies, improve digital literacy programs, and encourage ethical use of AI tools in order to fully realise AI's potential in academic information sourcing. Recommendations include investing in technology infrastructure, providing targeted training on AI tool usage, and fostering a culture of responsible AI use to improve academic outcomes and research efficiency.

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