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article · Artificial Intelligence in Education

Awareness and use of large language models among library and information science (LIS) students: implications for LIS educators

2025Open accessKwara State University

Abstract

Purpose Applications of innovative technologies have been proven to assist students in their academic performance. Meanwhile, this study examined the awareness and use of large language models (LLMs) among library and information science (LIS) students of Kwara State University (KWASU), Malete. Design/methodology/approach The study adopts a descriptive survey research design, with a population of 1,479. The questionnaire was adopted as a data collection instrument. The sample size is 306 undergraduates. Out of the 306 copies of the questionnaire administered, only two hundred and seventy-nine (279) were retrieved. Findings The findings revealed that the LIS undergraduate students were aware of Google Gemini, ChatGPT and LLMs in general. The findings indicated that LIS undergraduate students extensively used ChatGPT among the LLMs. The findings demonstrated that the purpose of using LLMs among LIS undergraduate students include academic work, solving complex questions, quick answers to questions, paraphrasing and summarizing and grammar checks. The study found that the challenges faced by students include technical issues, plagiarism, ethical issues, false information, the possibility of output bias and privacy and security. Practical implications The study suggests that LIS educators need to acknowledge the growing presence of LLMs in the educational landscape. Hence, policies should incorporate these technologies into their educational planning and curricula. Training and re-training can be provided to provide insights on the applications, benefits and limitations of LLMs. Originality/value The study provides insights on the use of LLMs among undergraduate students, guiding theoretical and practical discussions on students’ awareness and use of LLMs for academic activities.

Research topics

  • AI in Service Interactions
  • Topic Modeling
  • Knowledge Management and Sharing

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DOI: 10.1108/aiie-11-2024-0041

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