Impact of Constructive and Blended Video-Based Learning for Programming Using Generative AI

Abstract

This paper introduces COVIA (Code + Video + AI), a constructive Video-Based Learning (VBL) platform aiming to address ongoing challenges in computer science education, particularly those related to student engagement and instructor workload. The system was deployed in a blended learning setting as supplementary instruction in mandatory introductory programming courses at a university in Mexico. Curriculum materials and videos were designed using a human-in-the-loop workflow assisted by Generative AI (GenAI) and validated by subject-matter experts. This study employs a longitudinal, quasi-experimental quantitative design, complemented by a quantitative acceptance assessment based on the Technology Acceptance Model (TAM). The evaluation focused on three distinct phases of the introductory Java curriculum: (1) Language Elements, (2) Selective Structures, and (3) Iterative Structures. Statistical analysis using the Wilcoxon Signed-Rank test confirmed that the Experimental Group achieved highly significant learning gains across all three phases ((Formula presented.)). In contrast, the Control Group failed to achieve statistically significant growth in Phase 1 ((Formula presented.)) and Phase 3 ((Formula presented.)). In conclusion, the results suggest that the COVIA platform supports the development of introductory programming competencies as a supportive tool within a blended instructional framework.