Collaborative software development projects are central to contemporary computer science education, as they mirror industry practices and cultivate essential teamwork competencies. Despite their pedagogical value, evaluating and improving collaboration in academic settings remains challenging due to the subjective nature of teamwork assessment and the difficulty of attributing individual contributions. This study examines the role of visual analytics as a systematic, data-driven approach for measuring, monitoring, and enhancing collaborative software development in academic environments. Through a structured synthesis of prior research in visual analytics, software engineering education, and collaborative learning, the paper proposes a conceptual framework that maps development artifacts such as version control activity, issue tracking data, and communication logs to interpretable visual representations. The analysis demonstrates how visual analytics can support objective assessment, formative feedback, and reflective learning by revealing participation patterns, collaboration dynamics, and process inefficiencies. The study further discusses pedagogical implications, integration challenges, and ethical considerations associated with deploying visual analytics in academic workflows. The findings position visual analytics as a scalable and pedagogically meaningful mechanism for improving fairness, transparency, and learning outcomes in team-based software development education.`