Eye-Based Construct Measurement and Its Validity
Feiyan Jia et al.
What the paper says
Objective eye movement data have the potential to measure users' states instantly and in real time, providing a basis for timely intervention and personalized adaptation. Despite the broad applicability of eye-based construct measurement, research on its development and validation remains limited. Following the preferred reporting items for systematic reviews and meta-analyses guidelines, this review analyzes 127 studies that investigate the use of eye-tracking metrics to measure abstract constructs and the corresponding validity evidence. The findings reveal that eye-tracking metrics can measure a wide variety of constructs. Drawing on validity evidence commonly employed in psychometric-based construct measurement, this study synthesizes and summarizes validity evidence applicable to eye-based construct measurement. To illustrate the application of eye-tracking metrics and their supporting evidence, this article uses the example of detecting a vehicle driver's cognitive load, offering guidance for future studies and practical applications.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.