AI-supported pedagogical pipeline for computing students’ research competence

Abstract

This study evaluates an artificial intelligence (AI)-enabled co-curricular student club model implemented at two regional universities, organized as a staged four-part pipeline comprising competitive programming, hackathon prototyping, startup/project development, and final project defense. A matched pre/post design was used to assess changes in students’ objective computing knowledge, measured through a supervised computing skills test, and self-reported constructs, measured through an AI literacy and learning disposition survey. Outputs from club activities were also documented and combined into an OutputsIndex. The analyses showed statistically significant improvements in both computing knowledge and survey-based constructs, indicating that the intervention strengthened both foundational technical competence and students’ readiness for applied, performance-based work. AI literacy was also significantly associated with both knowledge scores and real-life outcomes, even after controlling for site and baseline differences, indicating that students with stronger AI-related competencies applied their learning more effectively to performance-based outputs. The findings support the potential of scalable, evidence-based IT student pipelines in Kazakhstan’s higher education context, and suggest that structured, AI-supported pathways can align skill development with responsible AI use, stronger learning outcomes, and measurable real-world performance.