PIVO engagement 2023 2024

 Contribution: This study introduces a mandatory practical programming exam and evaluates its impact on student learning outcomes. It also presents \\textbf{Programmers' Interactive Virtual Onboarding (PIVO), a self-made Automated Programming Assessment System (APAS), designed to facilitate structured practice and automated feedback. Findings demonstrate how enforced hands-on coding assessment improves programming proficiency while self-driven engagement in non-mandatory assignments enhances both theoretical and applied learning.Background: Traditional programming courses often emphasize theoretical understanding, neglecting hands-on coding experience. Limited practice opportunities and lack of immediate feedback contribute to low retention and skill acquisition. This study addresses these challenges by incorporating structured, automated assessment to provide scalable feedback and simulate real-world programming workflows. The research is applicable across global programming curricula where balancing theoretical knowledge with practical proficiency remains a challenge.Intended Outcomes: Improved student engagement, higher programming proficiency, stronger correlation between voluntary practice and exam performance, and increased pass rates in both written and practical assessments.Application Design: The approach combines automated formative assessment (PIVO), non-mandatory programming assignments, and a structured, supervised practical exam. PIVO enforces real-world coding constraints, limits resubmissions, and provides immediate feedback. The curriculum design follows a test-driven learning model, emphasizing iterative problem-solving.Findings: Implementation of the mandatory practical exam resulted in a significant decrease in failure rates. Statistical analysis shows a moderate to strong correlation between engagement in non-mandatory programming tasks and exam performance. Results indicate that structured, practice-driven assessment improves algorithmic thinking and problem-solving skills. Future work explores test-driven learning methodologies and strategies to adapt assessments to AI-generated code.