BJAR British Journal of Advanced Research BJAR 3153-709X Ivory and Finch Publishers 10.68263/BJAR-DZP76H4G BJAR_AUG_26_001 Original Research Article Effectiveness of Meta AI, Chat GPT and Gemini AI in Life Science Technology, Teaching and Library Material, A Novice-Friendly Comparison Edache Ehoche Elijah https://orcid.org/0000-0002-7821-3220 Science and Laboratory Technology Department, Federal Polytechnic Ugep, Nigeria. elaijahee@gmail.com Joseph Ita Library and information Science Department, Federal Polytechnic Ugep Johnson Adejoh Biochemistry Department, University of Abuja, Abuja Josephine Eban Nneayeba Science and Laboratory Technology Department, Federal Polytechnic Ugep William Eko Elizabeth Science and Laboratory Technology Department, Federal Polytechnic Ugep Elijah Dorcas Electrical Electronics Engineering Department, Federal University of Technology Minna 14 08 2026 1 2

Large Language Models (LLMs) are increasingly being used to enhance teaching and learning. This work focused on the Effectiveness of Meta(A), Gemini (B), and ChatGPT (C) AI in Life Science Library and Teaching Material. A prompt was used to generate AI data in the various LLMs, and the data was analyzed for validity, engagement and timeliness to measure the effectiveness and efficiency. 10 students were engaged, and a well-qualified, experienced processional teacher was engaged in the assessment. The personnel assessed the validity and appropriateness, and the students assessed the engagement capacity as well as the comprehensiveness of the generated data. Both used a 5-point Likert scale. Further analysis, which includes the time of generation. Examples and question count, descriptive statistics, and inferential statistics(Friedman ranking) were done with the aid of AI-assisted Excel software. Apart from the count, the results showed that ChatGPT and Gemini AI proved more effective. Most of the tested data proved that there is no significant difference between the values(p<0,05). This information is crucial for students, lecturers, Liberians and teachers, especially where resources and the environment are limited for learning.

 Artificial Intelligence Large Language Models Life Science Education Comparative Analysis Educational Technology 01 08 2026 07 08 2026 Copyright © 2026 by the authors This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. References Alkaissi, A., &amp; McFarlane, S. I. (2023). Artificial hallucinations in ChatGPT: Implications in scientific writing. _Cureus, 15_(2), e35179. https://doi.org/10.7759/cureus.35179 Baidoo-Anu, D., &amp; Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. _Journal of AI, 7_(1), 52–62. https://doi.org/10.61969/jai.1337500 Bhat, S., Singh, S., &amp; Kumar, R. (2024). Chat GPT, Gemini or Meta AI: A comparison of AI platforms as a tool for answering higher-order questions in microbiology. _Journal of Postgraduate Medicine_. https://doi.org/10.4103/jpgm.jpgm_775_24 Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. _International Journal of Educational Technology in Higher Education, 20_(1), 38. https://doi.org/10.1186/s41239-023-00408-3 Chiu, T. K. F. (2023). The impact of generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. _Interactive Learning Environments_. https://doi.org/10.1080/10494820.2023.2253861 Dai, Y., Liu, A., &amp; Lim, C. P. (2023). Reconceptualizing ChatGPT and generative AI as a student-driven innovation in higher education. _Procedia CIRP, 119_, 84–90. https://doi.org/10.1016/j.procir.2023.05.002 Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... &amp; Wright, R. (2023). "So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI. _International Journal of Information Management, 71_, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642 Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... &amp; Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. _Learning and Individual Differences, 103_, 102274. https://doi.org/10.1016/j.lindif.2023.102274 Kaur, G., &amp; Sharma, P. (2025). Comparative performance of ChatGPT, Gemini, and final-year emergency medicine clerkship students in answering multiple-choice questions. _International Journal of Emergency Medicine, 18_, 42. https://doi.org/10.1186/s12245-025-00789-1 Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., ... &amp; Tseng, V. (2023). Performance of ChatGPT on USMLE: Potential for AI-assisted medical education. _PLOS Digital Health, 2_(2), e0000198. https://doi.org/10.1371/journal.pdig.0000198 Okonkwo, C., &amp; Patel, R. (2024). Comparison of Large Language Models in Generating Machine Learning Curricula in High Schools. _Education Sciences, 14_(8), 845. https://doi.org/10.3390/educsci14080845 Salvagno, M., Taccone, F. S., &amp; Gerli, A. G. (2023). Can artificial intelligence help for scientific writing? _Critical Care, 27_(1), 75. https://doi.org/10.1186/s13054-023-04380-2 Zhu, Y., Wu, Y., Zhao, L., &amp; Zheng, Y. (2023). A comparative study of ChatGPT and other AI tools in educational applications. _Education and Information Technologies_. https://doi.org/10.1007/s10639-023-12185-2