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 ($p<0.001$). In contrast, the Control Group failed to achieve statistically significant growth in Phase 1 ($p=0.119$) and Phase 3 ($p=0.448$). 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.