ARTIFICIAL INTELLIGENCE AND ACADEMIC STRESS REDUCTION AMONG UNDERGRADUATE STUDENTS: EVIDENCE FROM PRINCE ABUBAKAR AUDU UNIVERSITY, ANYIGBA, KOGI STATE, NIGERIA

This study examined the influence of Artificial Intelligence (AI) on academic stress reduction as perceived by undergraduate students of Prince Abubakar Audu University, Anyigba, Kogi State, Nigeria. The study was anchored on the Technology Acceptance Model and Cognitive Load Theory. A mixed-methods, descriptive survey design was adopted, and a multi-stage sampling technique was used to select 380 undergraduates from the Faculties of Management Sciences, Social Sciences and Natural Sciences, with the sample size determined using Krejcie and Morgan's formula. Primary data were obtained through structured questionnaires and in-depth interviews, while secondary data were drawn from journals, textbooks and other relevant publications. Quantitative data were analysed using frequencies, percentages, mean scores, chi-square and independent samples t-test, while qualitative data from the interviews were analysed thematically. Findings revealed a high prevalence of AI usage among undergraduates, with ChatGPT the most widely used tool, followed by Meta AI, Google Gemini, Grammarly, Microsoft Copilot, QuillBot and Photomath. Students reported using these tools mainly to generate ideas, summarise lecture notes, improve writing, solve academic problems and prepare for examinations. Hypothesis testing revealed a statistically significant relationship between the prevalence of AI usage and academic stress reduction (χ² = 43.805, df = 1, p < .001) and between patterns of AI usage and academic stress reduction (χ² = 96.755, df = 1, p < .001), while no significant difference was found in the reduction of academic stress between male and female undergraduates (t(378) = -0.542, p = .588). The study concluded that artificial intelligence has become an important academic resource that contributes meaningfully to reducing academic stress among undergraduates when used responsibly. It recommended that university management should organise regular AI training programmes, strengthen digital infrastructure and develop clear policies guiding the ethical and effective use of artificial intelligence among students.