Source Data - Cleaned - Predictive Factors in Team Formation in Software Engineering Education: A Ten-Year Longitudinal Study of Student Attributes and Performance

To provide a multi-dimensional view of student performance and team dynamics, the research team tracks a comprehensive set of attributes for each student. This dataset moves beyond broad binary indicators of technical experience by capturing specific proficiencies, development orientations, and self-assessed leadership styles. The datasets describe candidates across five primary dimensions, beginning with Academic Attributes such as normalized undergraduate GPA, university prestige, and country of origin. This is complemented by Technical Experience, which considers self-reported proficiency in frontend, backend, or full-stack development along with familiarity in specific frameworks like Node.js and Java. To ensure collaborative success, we measure Communication Fluency on a 4-point scale (ranging from Very Comfortable to Very Uncomfortable) and assess Leadership Dynamics based on individual roles and preferences. Finally, performance is validated through Peer Evaluation Ratings sourced from CATME, which specifically track contributions to the team, interpersonal interaction, ability to keep the project on track, possession of relevant KSAs (Knowledge, Skills, and Abilities), and a consistent expectation of quality.