Zubair Ahsan
ABSTRACT
The studies on program comprehension using eye-tracking technology have not largely used Scanpath Trend Analysis (STA) to generate common scanpaths for a group of specific expertise in programming comprehension studies. It is important to understand the applicability of STA to help educators distinguish the reading orders of individuals as they solve programming tasks to develop better educational materials and improve instruction. In this research work, we conducted an experiment using common fundamental programming questions on 66 undergraduate computer science students to study the gaze behavior among the novices (high and low performing) on programming comprehension. We aim to better understand the navigation behavior between groups of high and low performers’ common scanpaths generated by STA and whether Hierarchical Cluster Analaysis (HCA) can cluster these common scanpaths for high- and low-performing individuals across different stimuli. Findings suggest that the STA algorithm is a technique to consider to find common representative scanpaths of a group of individuals, however, HCA with relative Levenshtein distance metric alone may not be suitable to cluster high and low performers groups for varying numbers of AOIs across different stimuli.
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Index Terms
- Is Clustering Novice Programmers Possible? Investigating Scanpath Trend Analysis in Programming Tasks
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