AI Readiness Among Pre-Service Teachers in Kaduna State: Awareness, Attitudes, and Motivating Factors for Curriculum Delivery

Abstract

The global integration of artificial intelligence (AI) into educational systems has generated 
urgent questions about whether pre-service teachers are sufficiently prepared to harness 
these technologies for effective curriculum delivery. This study assessed AI readiness among 
pre-service teachers in Kaduna State: Awareness, attitudes, and motivating factors for 
curriculum delivery, investigating three critical dimensions: awareness of AI tools, attitudes 
toward AI adoption, and the factors motivating AI adoption. A descriptive survey research 
design was adopted, with a target population of approximately 2,500 final-year pre-service 
teachers drawn from three purposively selected tertiary institutions, that is, Ahmadu Bello 
University [ABU], Zaria, Kaduna State University (KASU) and Kaduna State College of 
Education (KSCOE) Gidan Waya. Using the Yamane (1967) formula, a sample of 348 
respondents was obtained through stratified random sampling. Data were collected via a 
validated researcher-developed instrument, the Artificial Intelligence Readiness Assessment 
Questionnaire for Pre-Service Teachers (AIRAQPST), rated on a four-point Likert scale. The 
instrument yielded a Cronbach’s Alpha reliability coefficient of 0.87. Descriptive statistics 
(means and standard deviations) addressed the research questions, while One-Way Analysis 
of Variance (ANOVA) tested the null hypotheses at a 0.05 significance level. Findings 
revealed a moderate level of AI tool awareness among pre-service teachers (cluster mean = 
2.76), predominantly positive attitudinal orientations toward AI adoption (cluster mean = 
3.29), and strong motivational dispositions underpinning AI adoption in curriculum delivery 
(cluster mean = 3.37). ANOVA results indicated no significant institutional difference in 
awareness levels [F(2, 345) = 1.48, p = .229], while significant inter-institutional differences 
were observed in attitudes [F(2, 345) = 3.74, p = .024] and motivating factors [F(2, 345) = 
4.12, p = .017]. The study recommends systemic integration of AI literacy within teacher 
education curricula, targeted infrastructure investment, and robust institutional policy 
frameworks to advance effective AI adoption across tertiary institutions in Kaduna State. 
However, the findings are constrained by the study’s cross-sectional design, reliance on self
report data, and focus on final-year students in three Kaduna-based institutions, which may 
limit generalizability.