Natural Language Processing for Agriculture-Based Industrial Skills Development in Polytechnics
Main Article Content
Keywords
Artificial Intelligence, Natural Language Processing, Agric-based industrial skill
Abstract
Machines are created to execute tasks naturally required to be done by the natural intelligence of human, this is known as Artificial Intelligence (AI). Using generative AI in TVET (Technical and Vocational Education and Training) promotes lifelong learning and digital literacy. However little research has been done on how Nigerian agriculture students use Natural Language Processing (NLP) AI tools like ChatGPT, Meta AI and DeepSeek. This study looked at the social-demographic of Agric-based students, usage patterns effects and difficulties of NLP AI tools among Nigerian polytechnic students enrolled in agriculture-related programs. Data were gathered from 300 students using structured questionnaires and a descriptive quantitative design. The results showed that 50% had a National Diploma 2 and 43% were between the ages of 20 and 22. Research (60%) assignments (30%) and learning (30%) were the main uses of NLP tools with ChatGPT (35%) and Meta AI (56%) being the most popular. Significant gains in comprehension (88.70%) application (93.20%) and problem-solving abilities (76.60%) associated with agricultural capabilities were reported by respondents. Students faced obstacles like restricted access technical problems and trouble understanding AI-generated content in spite of these advantages. If inclusive access and usability are improved the results demonstrate the revolutionary potential of AI in agricultural TVET. It is advised that Nigerian agricultural sector especially in polytechnic education benefit from the strategic application of NLP AI tools.
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Josiah Oyekale, Federal Polytechnic Ilaro, Ogun State Nigeria
Dr. J. I. Oyekale is a Lecturer in the Department of Crop Production, Federal Polytechnic Ilaro, Ogun State, Nigeia. He holds a Ph.D. in Crop Biotechnology from Babcock University Ilishan-Remo Ogun State. He has over 5 years of experience in research collaborations and academic writing. His areas of expertise include Crop Production and Biotechnology. He can be communicated via email at josiah.oyekale@federalpolyilaro.eud.ng. ORCID: 0000-0002-8895-8592.
Muyiwa Okusanya, Federal Polytechnic Ilaro, Ogun State Nigeria
Engr. M. A. Okusanya currently serves as the Head, Department of Agricultural and Bioenvironmental Engineering, Federal Polytechnic Ilaro, Ogun State, Nigeria. He holds a Master of Science degree in Agricultural and Environmental Engineering from the University of Ibadan, where he is presently in his third year of doctoral studies in the same discipline. With a decade of experience in teaching and research, he has made notable scholarly contributions, including the authorship of three widely circulated books. He also holds four patents in areas spanning plastic waste recycling, palm oil processing technology, and IoT-enabled egg incubation and hatching systems. He can be reached via email at: muyiwa.okusanya@federalpolyilaro.edu.ng ORCID: 0000-0002-1922-5213
Oluwaseun Fase, Federal Polytechnic Ilaro, Ogun State Nigeria
O.B. Fase is a lecturer in the Department of Crop Production, Federal Polytechnic Ilaro, Ogun State, Nigeria. She holds a Bachelor's degree in Crop Production and Master's degree in Oil and Gas Management from Oil and Gas Management from South America University, Delaware, United States of America. He has over 5 years of experience in research collaborations and academic writing. Her area of expertise includes Crop Production and Oil and Gas Management. She can be communicated via email at Oluwaseun.fase@federalpolyilaro.edu.ng
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