Using Eye Movement Data Visualization to Enhance Training of Air Traffic Controllers: A Dynamic Network Approach

Classification framework to identify similar visual scan paths using multiple similarity metrics

Analyzing visual scan paths, the time-ordered sequence of eye fixations and saccades, can help us understand how operators visually search the environment before making a decision. To analyze and compare visual scan paths, prior studies have used metrics such as string edit similarity, which considers the order used to inspect areas of interest (AOIs), as well as metrics that consider the AOIs shared between visual scan paths. However, to identify similar visual scan paths, particularly in tasks and environments in which operators may apply variations of a common underlying visual scanning behavior, using solely one similarity metric might not be sufficient. In this study, we introduce a classification framework using a combination of the string edit algorithm and the Jaccard coefficient similarity. We applied our framework to the visual scan paths of nine tower controllers in a highfidelity simulator when a "clear-to-take-off" clearance was issued. The classification framework was able to provide richer and more meaningful classifications of the visual scan paths compared to the results when using either the string edit algorithm or Jaccard coefficient similarity.

The Effects of Language Barriers and Time Constraints on Online Learning Performance: An Eye-Tracking Study

OBJECTIVE

The goal of this study is to model the effect of language use and time pressure on English as a first language (EFL) and English as a second language (ESL) students by measuring their eye movements in an on-screen, self-directed learning environment.

BACKGROUND

Online learning is becoming integrated into learners' daily lives due to the flexibility in scheduling and location that it offers. However, in many cases, the online learners often have no interaction with one another or their instructors, making it difficult to determine how the learners are reading the materials and whether they are learning effectively. Furthermore, online learning may pose challenges to those who face language barriers or are under time pressure.

METHOD

The effects of two factors, language use (EFL vs. ESL) and time constraints (high vs. low time pressure), were investigated during the presentation of online materials. The effects were analyzed based on eye movement measures (eye fixation rate-the total number of eye fixations divided by the task duration and gaze entropy) and behavioral measures (correct rate and task completion time).

RESULTS

The results show that the ESL students had higher eye fixation rates and longer task completion times than the EFL students. Moreover, high time pressure resulted in high fixation rates, short task completion time, low correct rates, and high gaze entropy.

CONCLUSION AND APPLICATION

The results suggest the possibility of using unobtrusive eye movement measures to develop ways to better assist those who struggle with learning in the online environment.