Effect of AI-Supported Troubleshooting Instruction on Students’ Diagnostic Skills in Basic Electronics in Minna Institute of Technology and Innovation

Abstract

The study investigated the effect of AI-supported troubleshooting instruction on students’ diagnostic skills in Basic Electronics in Minna Institute of Technology and Innovation. The study adopted a quasi-experimental research design, specifically a pre-test, post-test non-equivalent control group design. The population of the study comprised 130 students offering Basic Electronics-related courses at Minna Institute of Technology and Innovation. Census sampling technique was adopted because the population was manageable, and the entire 130 students participated in the study, comprising 69 students in the AI-supported instruction group and 61 students in the conventional instruction group. Data were collected using a researcher-developed Basic Electronics Diagnostic Skills Test (BEDST), which assessed students’ fault-identification, fault-analysis and rectification skills. The instrument was validated by experts in Electrical and Electronics Technology Education and Measurement and Evaluation. A pilot test was conducted using 25 Electrical and Electronics Technology Education students of Niger State College of Education, Minna, who were not part of the main study. A reliability coefficient of 0.79 was obtained using Cronbach’s alpha, indicating acceptable internal consistency. The experimental group received AI-supported troubleshooting instruction, while the control group received conventional instruction. Mean and standard deviation were used to answer the research questions, while Analysis of Covariance (ANCOVA) was used to test the hypotheses at 0.05 level of significance. The findings indicated that students exposed to AI-supported troubleshooting instruction recorded greater improvement in fault-identification, fault-analysis and rectification skills than those exposed to conventional instruction. The study concluded that AI-supported troubleshooting instruction had significantly enhanced students’ diagnostic skills in Basic Electronics. It was recommended that technical education institutions should integrate structured AI-supported troubleshooting activities into Basic Electronics instruction while maintaining adequate hands-on practical activities and teacher supervision.