• Media type: E-Article
  • Title: Studying Developer Eye Movements to Measure Cognitive Workload and Visual Effort for Expertise Assessment
  • Contributor: Aljehane, Salwa D.; Sharif, Bonita; Maletic, Jonathan I.
  • Published: Association for Computing Machinery (ACM), 2023
  • Published in: Proceedings of the ACM on Human-Computer Interaction, 7 (2023) ETRA, Seite 1-18
  • Language: English
  • DOI: 10.1145/3591135
  • ISSN: 2573-0142
  • Keywords: Computer Networks and Communications ; Human-Computer Interaction ; Social Sciences (miscellaneous)
  • Origination:
  • Footnote:
  • Description: <jats:p>Eye movement data provides valuable insights that help test hypotheses about a software developer's comprehension process. The pupillary response is successfully used to assess mental processing effort and attentional focus. Relatively little is known about the impact of expertise level in cognitive effort during programming tasks. This paper presents a quantitative analysis that compares the eye movements of 207 experts and novices collected while solving program comprehension tasks. The goal is to examine changes of developers' eye movement metrics in accordance with their expertise. The results indicate significant increase in pupil size with the novice group compared to the experts, explaining higher cognitive effort for novices. Novices also tend to have a significant number of fixations and higher gaze time compared to experts when they comprehend code. Moreover, a correlation study found that programming experience is still a powerful indicator when explaining expertise in this eye-tracking dataset among other expertise variables.</jats:p>