Teachers’ Knowledge and Attitude Toward Artificial Intelligence as a Correlate of Teaching Effectiveness in Senior Secondary Schools in Delta State

Attitude Toward Artificial Intelligence

Abstract

This study examined the influence of teachers’ knowledge and attitude towards Artificial Intelligence (AI) tools on teaching effectiveness in senior secondary schools in Delta State, Nigeria. Motivated by the persistent underutilization of AI tools in Nigerian secondary school classrooms despite their acknowledged transformative potential, the study investigated the level of teachers’ AI knowledge, the nature of their attitude towards AI, and the extent to which these variables relate to teaching effectiveness. Grounded in the Technology Acceptance Model (TAM) and the Technological Pedagogical Content Knowledge (TPACK) framework, the study adopted a descriptive survey design. A sample of 360 teachers was drawn from public senior secondary schools using a multi-stage sampling technique. Data were collected using the Teachers’ Knowledge, Attitudes toward Artificial Intelligence, and Teaching Effectiveness Questionnaire (TKAITEQ), a researcher-developed instrument with established content validity (CVI = 0.87) and confirmed internal consistency (α = 0.79–0.84). Descriptive statistics and Pearson Product-Moment Correlation (PPMC) were employed for data analysis. Findings revealed that teachers’ knowledge of AI was generally low (grand mean = 2.18), while their attitudes were cautiously positive but mixed (grand mean = 2.89), reflecting simultaneous recognition of AI’s educational potential and reservations about its feasibility in the Nigerian school context. Both null hypotheses were rejected at the .05 level of significance, denoting that teachers’ AI knowledge exhibited a strong positive relationship with teaching effectiveness (r = 0.671, p = 0.02), and teachers’ attitudes toward AI showed a moderate to strong positive relationship with teaching effectiveness (r = 0.58, p=.02). The study concludes that knowledge and attitudinal deficits are significant barriers to AI integration in the study area, and recommends the urgent provision of AI-focused professional development programmes, institutional support structures, and policy frameworks that address both the competency and motivational dimensions of teacher readiness for AI integration.