KNOWLEDGE, PERCEPTION AND USE OF ARTIFICIAL INTELLIGENCE AMONG STUDENTS OF UNIVERSITY OF BENIN, BENIN CITY, NIGERIA
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BACKGROUND: Artificial Intelligence (AI) is transforming higher education globally, yet data on AI knowledge, perception, and usage among Nigerian university students remain limited. Understanding these factors is essential for effective curriculum integration and preparing students for an AI-driven workforce.
OBJECTIVE: This study assessed the knowledge, perception, and use of Artificial Intelligence among students of the University of Benin, Benin City, Nigeria.
METHODS: A descriptive cross-sectional study was conducted among 603 undergraduate students selected using multistage random sampling from six faculties. Data were collected using a structured pretested, self-administered questionnaire and analysed with IBM SPSS version 27. Associations between sociodemographic factors and knowledge/perception/use were tested using chi-square and logistic regression, with statistical significance set at p < 0.05 (95% CI). RESULTS: The mean age of respondents was 19.9 ± 2.87 years and majority were females 355 (58.9%). Overall, 340 (56.4%) demonstrated good knowledge of AI, while 427 (70.8%) held positive perceptions. High AI usage was reported by 329 (54.6%) respondents, with ChatGPT being the most commonly used platform 450 (32.8%). Significant predictors of good knowledge included female sex (OR = 1.980, p = 0.001), being in the Faculty of Medicine (OR = 14.069, p = 0.001), and higher academic level (OR = 1.717, p = 0.020). Positive perception was significantly associated with high AI usage (OR = 8.020, p < 0.001) and excellent internet access (p = 0.041). AI usage was significantly influenced by positive perception (OR = 2.087, p = 0.025), peer interest (OR = 0.423, p = 0.004), and access to online learning platforms (OR = 0.528, p = 0.037). The most common concerns about AI were that it
OBJECTIVE: This study assessed the knowledge, perception, and use of Artificial Intelligence among students of the University of Benin, Benin City, Nigeria.
METHODS: A descriptive cross-sectional study was conducted among 603 undergraduate students selected using multistage random sampling from six faculties. Data were collected using a structured pretested, self-administered questionnaire and analysed with IBM SPSS version 27. Associations between sociodemographic factors and knowledge/perception/use were tested using chi-square and logistic regression, with statistical significance set at p < 0.05 (95% CI). RESULTS: The mean age of respondents was 19.9 ± 2.87 years and majority were females 355 (58.9%). Overall, 340 (56.4%) demonstrated good knowledge of AI, while 427 (70.8%) held positive perceptions. High AI usage was reported by 329 (54.6%) respondents, with ChatGPT being the most commonly used platform 450 (32.8%). Significant predictors of good knowledge included female sex (OR = 1.980, p = 0.001), being in the Faculty of Medicine (OR = 14.069, p = 0.001), and higher academic level (OR = 1.717, p = 0.020). Positive perception was significantly associated with high AI usage (OR = 8.020, p < 0.001) and excellent internet access (p = 0.041). AI usage was significantly influenced by positive perception (OR = 2.087, p = 0.025), peer interest (OR = 0.423, p = 0.004), and access to online learning platforms (OR = 0.528, p = 0.037). The most common concerns about AI were that it
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