This report presents the findings from the evaluation of the 2024 Virtual Lab Meetings (VLMs) conducted as part of the Data Jam Project. The assessment answers specific evaluation questions aimed at understanding the effectiveness and impact of the VLMs during the final program year. Analysis of the session transcripts identified trends in teacher participation, student data science skill development, and the impact of structured support on mentoring effectiveness.Student progress across three VLM cycles showed incremental improvements in graph construction, statistical interpretation, and evidence-based reasoning. Cross-disciplinary collaboration between math and science teachers enriched discussions but highlighted the need for more structured support to balance expertise across disciplines. Additionally, mentoring sessions were most effective when teachers submitted structured support tickets, leading to more focused and actionable discussions. The report concludes with recommendations to improve teacher engagement, mitigate routinization of protocols, enhance cross-disciplinary collaboration, and tailor mentoring strategies for both new and veteran educators. By refining session structures, incorporating advanced student skill-building activities, and leveraging interdisciplinary approaches, the Data Jam VLMs can continue fostering deeper learning and more impactful educational outcomes.