Speaker
Description
Lawrence, A. O.
Nigerian Army College of Education, Ilorin, Kwara State, Nigeria
olutosinadebayi@gmail.com
Track: AI, Emerging Technologies and Future Learning
By
ADEBAYO, Olutosin Lawrence
Department of Physics Education,
Nigerian Army College of Education (NACOE), Ilorin
Phone No: 08028140328, 08130057203
E-mail: olutoinadebayi@gmail.com
Abstract
This study examined the influence of AI-powered adaptive learning systems, intelligent tutoring systems, and AI-based assessment tools on competency attainment, and learners’ skill acquisition. A descriptive survey research design was adopted. The population comprised 985 students, 76 NCE students and 909 degree students of the Nigerian Army College of Education (NACOE), Ilorin. A sample size of 285 respondents was selected using the Krejcie and Morgan sample size determination table, while proportionate sampling technique was used to allocate the sample to the NCE and degree programmes, simple random sampling technique was employed to select the respondents from each category. A structured questionnaire with a reliability coefficient of 0.91 was used to collect data. Pearson Product Moment Correlation (PPMC) was employed to test the three hypotheses at the 0.05 level of significance. The findings revealed a significant positive relationship between AI-powered adaptive learning systems and competency attainment (r = 0.721, p = 0.002); intelligent tutoring systems and teaching effectiveness (r = 0.689, p = 0.004); and AI-based assessment and feedback tools and learners’ skill acquisition (r = 0.754, p = 0.001). The results indicated that the corresponding coefficients of determination were 52.0%, 47.5%, and 56.9%, respectively, implying that the selected AI-driven educational technologies accounted for substantial variations in competency attainment, teaching effectiveness, and skill acquisition among the respondents. The study concluded that artificial intelligence-driven education technologies significantly enhance competency-based teaching and learning. Based on these findings, the study recommended, among others, that educational institutions should mainstream AI-driven learning technologies into classroom instruction.
Keywords: competency-based learning, AI-powered adaptive learning systems, intelligent tutoring systems, AI-based assessment and feedback, skill acquisition