Technical and vocational education teachers computer competencies using artificial intelligence - IDRIS ADAMU; SEZER KANBUL; ADAMU GAMBO; TAHIRU ZANNA (Journal of Advanced Research in Social Sciences and Humanities, 2020)
Aim: This article investigates the knowledge and skills required by teachers of Technical and Vocational Education (TVE) to effectively implement computers and related technologies in the classroom.Method: The survey used a structured questionnaire with 44 items about the participant’s knowledge, opinions, and feelings regarding computer operation. TVE instructors at six different northern Nigerian tertiary technical institutions were each given one of sixty questionnaires to administer to their teachers (Bauchi and Gombe). Multilinear Regression (MLR) and Artificial Intelligence (AI) techniques, such as Artificial Neural Networks (ANN) and an Adaptive Neuro-fuzzy Inference System (ANFIS), were used to analyze the data (ANFIS). While the ANN and ANFIS models were developed using MATLAB 9.3 (R2019a), the classical linear MLR model was created in SPSS.Findings: The results show that teachers in technical and vocational fields are highly proficient in using digital tools, with a strong relationship between competence and teaching experience and a weaker relationship between competence and gender.Implications/Novel Contribution: This will help scholars, administrators, and teachers in Nigeria, as well as the Nigerian Ministry of Education