HARNESSING ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE EDUCATIONAL DEVELOPMENT: PHYSICAL AND HEALTH EDUCATION TEACHERS' READINESS FOR AI INTEGRATION IN SPORTS PERFORMANCE ANALYSIS IN KANO STATE, NIGERIA

Abstract

The study examined the level of awareness and readiness of physical and health education (PHE) teachers for integrating artificial intelligence (AI) into sports performance analysis, with a view to drawing implications for sustainable educational development. Anchored on the Technology Acceptance Model (Davis, 1989) and the Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003), the study adopted a descriptive survey design. A sample of 220 PHE teachers was drawn from government secondary schools in Kano State, Nigeria, using a stratified random sampling technique guided by the Krejcie and Morgan (1970) table for sample size determination. Data were collected with a structured, validated instrument, the AI Readiness and Perception Questionnaire for Sports Performance Analysis (AIRPQ-SPA), which yielded an overall Cronbach's alpha of .81. Data were analysed using descriptive statistics, an independent-samples t-test, a one-way analysis of variance (ANOVA), and Pearson product-moment correlation. Findings revealed a moderate level of awareness of AI applications among teachers ($M = 2.86, SD = 0.54$) but a comparatively lower level of readiness to integrate such tools into practice ($M = 2.61, SD = 0.61$). Inadequate infrastructure, insufficient training, the high cost of AI-enabled devices, and unstable internet connectivity emerged as the most pressing perceived barriers. Readiness did not differ significantly by gender, $t(218) = 1.42, p = .157$, but differed significantly by years of teaching experience, $F(2, 217) = 4.87, p = .009$, with less experienced teachers reporting greater readiness. A significant, moderate, positive relationship was found between awareness and readiness, $r(218) = .52, p < .001$. The study concluded that awareness of AI is a necessary but insufficient condition for its integration into sports performance analysis and recommends targeted professional development, infrastructural investment, and supportive institutional policy to enable PHE teachers to harness AI for sustainable educational development.