Abstract
The growing demand for Big Data and artificial intelligence competencies requires new instructional approaches in higher education. This study investigates the pedagogical effectiveness of an AI-integrated, competency-based instructional model implemented through projects. The research was guided by three research questions addressing the structure of professional competencies, the design of a pedagogical model, and its educational effectiveness. The study employed a design-based research approach and involved 22 undergraduate computer science students. Students’ competencies were assessed using a rubric-based, artifact-oriented evaluation system covering data collection, analysis, modeling, interpretation, and scientific visualization. Quantitative data were analyzed using descriptive statistics and paired-samples t-tests, while qualitative project artifacts supported the interpretation of results. The findings demonstrate significant improvement in students’ conceptual understanding and high levels of competency in final reports, particularly in data preparation and visualization. The results indicate that AI-integrated learning effectively supports the development of professional competencies in Big Data education.