Artificial intelligence as a pedagogical tool for developing research competence in pre-service English language teachers

The growing use of generative artificial intelligence (AI) in teacher education creates new opportunities for supporting research-related learning. However, limited empirical evidence exists on whether structured AI-supported pedagogy contributes to the research competence of pre-service English language teachers. A quasi-experimental pre-test–post-test control-group design was employed with 133 second-year pre-service English language teachers at Zhanibekov South Kazakhstan Pedagogical University, Kazakhstan. The experimental group ( n = 67) participated in an eight-week AI-supported research learning intervention, while the control group ( n = 66) received conventional research instruction. Research competence was assessed across four dimensions: methodological, cognitive, digital, and ethical. ANCOVA was used to describe baseline-adjusted differences between the two observed instructional cohorts. The AI-supported cohort had higher adjusted scores for overall research competence (adjusted difference = 1.338 points on a 0–36 scale), methodological competence (0.717 points on a 0–9 scale), and cognitive competence (0.924 points on a 0–9 scale). Adjusted digital and ethical competence scores were numerically lower in the AI-supported cohort, with differences of −0.153 and −0.247 points, respectively. Each condition was represented by a single instructional cluster, and condition was completely confounded with cohort membership. These contrasts therefore describe the two cohorts and cannot establish an intervention effect. The observed pattern warrants further investigation of structured activities requiring students to evaluate, verify, revise, and make independent decisions about AI-generated outputs as potential supports for methodological and cognitive research skills. Generative AI may support research competence when integrated as a pedagogical and cognitive scaffold rather than a substitute for independent reasoning. The findings highlight the importance of preserving critical judgement, verification, and student responsibility in AI-supported research education.