ASSESSING THE EEFECTIVENESS OF AI-BASED INSTRUCTIONAL TOOLS IN TEACHING OF AGRICULTURAL SCIENCE IN COLLEGES OF EDUCATION IN DELTA STATE: LECTURERS' PERCEPTION

Abstract This study assessed the effectiveness AI-Based instructional tools in teaching of Agricultural Sciences in Colleges of Education (COEs) in Delta State, looking at the lecturers’ perception. Three research questions guided the study. The study adopted a descriptive survey research design. The estimated population for this study comprised all the 68 Agricultural Science lecturers in the three public (one Federal and two State Government-owned) Colleges of Education in Delta State (that is: Federal College of Education (Technical), Asaba – 25 lecturers; Delta State College of Education, Mosogar – 26 lecturers; and Delta State College of Education, Warri – 17 lecturers). Sample size for the study comprised all the 68 lectures from the three COEs selected using a purposive sampling technique. The instrument for data collection was a researcher self-structured questionnaire titled “Effectiveness of AI-Based Instructional Tools in Teaching of Agricultural Science Questionnaire (EAIBITTASQ)” containing 29 items. Both validity and reliability of the questionnaire was established. Data collated were analyzed using mean (x̅) statistics and standard deviation (SD) statistics in order to answer the research questions. Findings of the study revealed among others that the AI-based instructional tools such as the intelligent tutoring systems, adaptive learning platforms, Agricultural simulation and visualization tools and learning analytics dashboards can be effectively utilized in teaching Agricultural Science in COEs in Delta State. Based on the findings, it was recommended among others that the Government (both federal and state), educational policymakers and other important education stakeholders should assist the colleges of education in Delta State through adequate resource mobilization to provide the necessary digital infrastructure (reliable internet, functional ICT labs, intelligent tutoring systems, adaptive learning platforms, virtual simulations, VR/AR tools, AI-enhanced LMS, and mobile AI tools, among others) alongside clear policies for ethical and sustainable use of AI-based instructional tools in teaching of Agricultural Science. This will ensure equitable access and maximize the positive impact of AI tools towards promoting effectiveness of teaching and learning in Agricultural Science in the COEs.