Assessing the Collaboration Quality in the Pair Program Tracing and Debugging Eye-Tracking Experiment

• Main Authors: Villamor, Maureen, Paredes, Yancy Vance, Samaco, Japeth Duayne, Cortez, Joanna Feliz, Martinez, Joshua, Rodrigo, Ma. Mercedes T
• Format: text
• Published: Archīum Ateneo 2017
• Subjects: Eye-tracking; Collaboration; Cross-recurrence quantification; Computer Sciences
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/59; https://www.researchgate.net/publication/318154749_Assessing_the_Collaboration_Quality_in_the_Pair_Program_Tracing_and_Debugging_Eye-Tracking_Experiment
• Institution: Ateneo De Manila University

We assessed the extent of collaboration of pairs of novice programmers as they traced and debugged fragments of code using cross-recurrence quantification analysis (CRQA). Specifically, we compared which among the pairs collaborated the most given a particular task. This was also a preliminary study that looked for patterns on how the pairs categorized according to expertise collaborated. We performed a CRQA to build cross-recurrence plots using the eye tracking data and computed for the CRQA metrics, such as recurrence rate (RR), determinism (DET), entropy (ENTR), and laminarity (LAM) using the CRP toolbox for MATLAB. Findings showed that Pair 3, which consisted of both high-performers, collaborated the most because of its highest RR and DET. However, its highest ENT and LAM implied that Pair 3 struggled the most in program comprehension. We found also that all the pairs as assessed through their RR’s started with low values, peaked in the middle, declined, and increased again when the task was about to end, regardless of how well partners knew each other prior to the task. This could mean that at the start the pairs were still independently assessing how to approach the task, then they started to collaborate once comfortable but then worked independently again in an attempt to finish.