Title:
An Empirical Exploration of Collaborative Performance in Engineering Learning Contexts [Download]Authors:
Oscar Revelo Sánchez, Manuel Ernesto Bolaños
Index Terms:
Abstract:
This study presents an empirical analysis of collaborative performance assessment in engineering learning scenarios. A validated instrument—derived from a previously developed questionnaire measuring seven operational dimensions of collaboration—was applied to evaluate group performance. The study involved 251 students from various engineering courses, organized into experimental groups based on personality traits and a control group formed according to student preference. Findings reveal that personality-based group formation influences collaborative performance, with outcomes varying by group configuration. Homogeneous and mixed groups emphasizing emotional stability (Neuroticism–N) demonstrated higher levels of leadership and collaboration, while heterogeneous groups underperformed compared to the control group. Across all formations, conflict management consistently emerged as the most challenging process, underscoring the importance of targeted strategies for managing interpersonal tensions in team-based learning. From a methodological standpoint, the assessment instrument exhibited high internal consistency (Cronbach’s $\alpha \gt 0.9$ ), affirming its reliability for evaluating collaborative dynamics in academic contexts. The study concludes that personality-informed group formation can optimize specific collaborative processes, though its effectiveness depends on the combination of personality traits within each team. These findings hold significant implications for the field of Human-Computer Interaction (HCI), particularly in informing the design of educational technologies that enable adaptive group formation and provide real-time feedback in collaborative learning environments.
DOI:
How to cite:
Oscar Revelo Sánchez, Manuel Ernesto Bolaños, "An Empirical Exploration of Collaborative Performance in Engineering Learning Contexts", IEEE-RITA, vol. 21, no. 1, pp. 54-63, Jan. 2026. doi: 10.1109/RITA.2026.3663552