An Exploration Of The Nexus Between Artificial Intelligence Assisted Learning And Undergraduate Students’ Performance In The Department Of Mass Communication, Federal University, Kashere
Published: 2025-08-30
Author(s): | Ayodele Babatunde Joseph |
Abstract: | This study examines the influence of Artificial Intelligence (AI) tools on academic performance among undergraduate students in the Department of Mass Communication at Federal University, Kashere. Guided by the Technology Acceptance Model (TAM), the research explores how students use AI platforms such as ChatGPT, Grammarly, and QuillBot, and evaluates the perceived
academic benefits and challenges associated with their use. A quantitative survey design was employed, and data were collected from a total population of 250 students. Out of these, 243 valid responses were analysed using descriptive statistical methods. The findings reveal that a majority of students frequently use AI tools mainly for writing assignments, proofreading, and research tasks—with many reporting improvements in assignment quality, understanding of topics, and completion speed. However, the study also identifies key challenges including poor internet access, limited AI literacy, inaccurate outputs, and a lack of institutional policies guiding ethical AI use. While most students support the formal integration of AI tools into academic practices, the absence of structured frameworks creates uncertainty and risk of misuse. The study concludes that AI tools are positively shaping learning experiences but require institutional support, digital skill development, and clear usage guidelines to maximise their educational value while preserving academic integrity. |
Keywords: | Artificial Intelligence, AI tools, Academic performance, Undergraduate students, Technology |
Edition | NJOMACS Volume 7 No 2, August 2025 |
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Copyright | Copyright © 2025 Ayodele Babatunde Joseph ![]() This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. |
Journal Identifiers
pISSN: 2635-3091