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Impostor Syndrome in Final Year Computer Science Students: An Eye Tracking and Biometrics Study

Alyssia Chen, Carol Wong, Katy Tarrit, Anthony Peruma

TL;DR

This study investigates imposter syndrome in final-year computer science students and its impact on code comprehension using augmented cognition methods. By combining eye-tracking and heart-rate biometrics with five Java code snippets and a customized Clance IP scale, it provides preliminary evidence that higher imposter syndrome correlates with longer reading times and lower accuracy, while also altering gaze behavior toward method-related code. The findings reveal gender differences in imposter-syndrome levels and establish a baseline dataset and methodology for interventions to improve student confidence and coding performance. The work offers practical implications for CS education and sets the stage for broader, industry-inclusive investigations into mental well-being and developer productivity.

Abstract

Imposter syndrome is a psychological phenomenon that affects individuals who doubt their skills and abilities, despite possessing the necessary competencies. This can lead to a lack of confidence and poor performance. While research has explored the impacts of imposter syndrome on students and professionals in various fields, there is limited knowledge on how it affects code comprehension in software engineering. In this exploratory study, we investigate the prevalence of imposter syndrome among final-year undergraduate computer science students and its effects on their code comprehension cognition using an eye tracker and heart rate monitor. Key findings demonstrate that students identifying as male exhibit lower imposter syndrome levels when analyzing code, and higher imposter syndrome is associated with increased time reviewing a code snippet and a lower likelihood of solving it correctly. This study provides initial data on this topic and establishes a foundation for further research to support student academic success and improve developer productivity and mental well-being.

Impostor Syndrome in Final Year Computer Science Students: An Eye Tracking and Biometrics Study

TL;DR

This study investigates imposter syndrome in final-year computer science students and its impact on code comprehension using augmented cognition methods. By combining eye-tracking and heart-rate biometrics with five Java code snippets and a customized Clance IP scale, it provides preliminary evidence that higher imposter syndrome correlates with longer reading times and lower accuracy, while also altering gaze behavior toward method-related code. The findings reveal gender differences in imposter-syndrome levels and establish a baseline dataset and methodology for interventions to improve student confidence and coding performance. The work offers practical implications for CS education and sets the stage for broader, industry-inclusive investigations into mental well-being and developer productivity.

Abstract

Imposter syndrome is a psychological phenomenon that affects individuals who doubt their skills and abilities, despite possessing the necessary competencies. This can lead to a lack of confidence and poor performance. While research has explored the impacts of imposter syndrome on students and professionals in various fields, there is limited knowledge on how it affects code comprehension in software engineering. In this exploratory study, we investigate the prevalence of imposter syndrome among final-year undergraduate computer science students and its effects on their code comprehension cognition using an eye tracker and heart rate monitor. Key findings demonstrate that students identifying as male exhibit lower imposter syndrome levels when analyzing code, and higher imposter syndrome is associated with increased time reviewing a code snippet and a lower likelihood of solving it correctly. This study provides initial data on this topic and establishes a foundation for further research to support student academic success and improve developer productivity and mental well-being.
Paper Structure (20 sections, 7 figures, 10 tables)

This paper contains 20 sections, 7 figures, 10 tables.

Table of Contents

  1. Introduction
  2. Goal & Research Questions
  3. Contribution
  4. Paper Structure
  5. Related Work
  6. Study Design
  7. Survey Design
  8. Code Snippets
  9. Eye Tracker & Biometric Device
  10. Data Preprocessing
  11. Participants
  12. Pilot Study
  13. Results
  14. RQ 1: To what extent are final-year undergraduate computer science students confident in their program comprehension skills?
  15. RQ 2: How does imposter syndrome affect the cognitive processes involved in comprehending code?
  16. ...and 5 more sections

Figures (7)

  • Figure 1: The five code snippets that were part of our study along with their associated question and answer choices.
  • Figure 2: Biometrics and Other Measures Averaged per IPC Group for Snippet 1
  • Figure 3: Biometrics and Other Measures Averaged per IPC Group for Snippet 2
  • Figure 4: Biometrics and Other Measures Averaged per IPC Group for Snippet 3
  • Figure 5: Biometrics and Other Measures Averaged per IPC Group for Snippet 4
  • ...and 2 more figures