Challenges and Prospects of Utilizing Artificial Intelligence into Teaching and Learning of Technical Education Courses in Tertiary Institutions in Kano State, Nigeria
The study focused on challenges and prospects of utilizing artificial intelligence into teaching and learning of technical education courses in tertiary institutions in Kano State, Nigeria. Two research questions guided the study and two null hypotheses were tested. A descriptive survey research design was adopted. The population of the study consisted of 206 technical educators in government owned tertiary institutions that offer technical education courses in Kano State. No sample was taken, as the population size was manageable. A 18-items structured questionnaire was used and validated by three experts for the study. The reliability of the instrument was ascertained using Cronbach Alpha which showed that the clusters achieved co-efficient values of 0.92 and 0.89 respectively for the clusters B1 and B2, with an overall reliability co-efficient value of 0.91. Data related to the research questions were analyzed using mean and standard deviation, while t-test was used to test the null hypotheses at 0.05 level of significance. The findings of the study revealed that challenges inhibiting the utilization of artificial intelligence into teaching and learning of technical education courses in tertiary institutions in Kano State, Nigeria to include lack of artificial intelligence literacy, access to artificial intelligence resources, inadequate infrastructure among others. The findings further revealed that utilizing artificial intelligence into teaching and learning of technical education courses in tertiary institutions in Kano State, Nigeria yields several prospects including advancements in adaptive learning systems that respond dynamically to individual student progress, enhancement of the personalization of education, among others. It was recommended among others that educational institutions should implement policies and guidelines for the controlled of challenges of utilizing artificial intelligent to ensure effective teaching and learning of technical education.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-17
- DOI
- https://doi.org/10.5281/zenodo.16948202
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00