Impact of AI-Based Learning Tools on Teaching Skills of ICT Teacher Trainees in Sri Lankan National Colleges of Education

Abstract

Artificial Intelligence (AI)-based learning tools are increasingly integrated into teacher training programmes worldwide, offering potential to enhance lesson planning, instructional delivery, assessment and reflective practices. However, empirical evidence regarding their association with teacher trainees, particularly within the Sri Lankan context, is limited. This study examines the association between AI-based learning tools and the teaching skills of ICT teacher trainees in Sri Lankan National Colleges of Education (NCoEs). A quantitative research design was employed, using a structured questionnaire administered to 112 second-year and third-year ICT teacher trainees at Ruwanpura National College of Education. Data were analyzed using descriptive statistics and Pearson correlation analysis. The findings indicate that AI-based learning tools were perceived to positively support lesson preparation (M = 4.12, SD = 0.68) and instructional delivery skills (M = 3.98, SD = 0.72), while relatively lower perceived support was observed in assessment (M = 3.54, SD = 0.81) and reflective practices (M = 3.47, SD = 0.79). A strong positive association was identified between AI tool usage and self-reported teaching skill development (r = 0.68, p < 0.01). These results highlight the necessity of structured integration of AI tools into teacher education programmes and the need for targeted training to maximize their effectiveness, particularly in assessment and reflective domains. The study contributes to the growing body of literature on AI in teacher education and provides practical implications for curriculum designers and policymakers in Sri Lanka. The main limitations are the single-institution convenience sampling and the use of self-reported measures.

Keywords

• Artificial Intelligence
• ICT Teacher Trainees
• Teaching Skills
• Teacher Education
• Sri Lanka