Beyond Gaze Data: Pupillometry as an Additional Data Source in Eye Tracking

Karch, Jessica M.

doi:10.1021/bk-2018-1292.ch008

Cited by 6 publications

(12 citation statements)

References 57 publications

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“…Deception, i.e., conscious violations of rules, can be however detected by pupillometry, hence ET technology can be used to identify potentially hazardous drivers. The combination of driving behavior and ET data demonstrated within the simulation can be further assessed in order to identify the potential psychopathic traits [107,108].…”

Section: Drivers Measures Using Eye-trackingmentioning

confidence: 99%

“…The distractions will be measured by ET based on the capturing specific fixations on the objects in the virtual environment (labeled as ET2) [68][69][70][71]. The Deception factor is represented by the conscious violation of traffic rules and could be identified based on a combination of ET1 and ET2 measures and activity log (e.g., driver saw speed sign but accelerated, considering also pupillometric measures to confirm consciousness rule violation) [108]. The situation awareness will be measured by wide logging and ET2 logging activity.…”

Section: Measures In Hmd-based Toolmentioning

confidence: 99%

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HMD-Based VR Tool for Traffic Psychological Examination: Conceptualization and Design Proposition

et al. 2021

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In the present theoretical paper, the current body of knowledge regarding the use of wearable virtual reality (VR) technologies for traffic psychological examination (TPE) is introduced, critically discussed and a specific application is suggested. The combination of wearable head-mounted displays for VR with an interactive and cost-effective haptic driving interface is emphasized as a valid and viable platform for a driving skills psychological assessment, which is in several aspects superior to standard TPE as well as driving simulators. For this purpose, existing psychological examination methods and psychological phenomena relevant in the process of driving are discussed together with VR technology’s properties and options. Special focus is dedicated to situation awareness as a crucial, but currently hardly measurable construct, where VR in combination with embedded eye-tracking (ET) technology represents a promising solution. Furthermore, the suitability and possibilities of these VR tools for valid traffic psychological examination are analyzed and discussed. Additionally, potentially desirable measures for driving assessment based on recent advances of VR are outlined and practical applications are suggested. The aim of this article is to bring together recent advances in TPE, VR and ET; revise previous relevant studies in the field; and to propose concept of the cost effective, mobile and expandable HMD-based driving simulator, which can be suitable for an ecologically valid driving assessment and follow-up TPE in common practice.

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Section: Drivers Measures Using Eye-trackingmentioning

confidence: 99%

Section: Measures In Hmd-based Toolmentioning

confidence: 99%

HMD-Based VR Tool for Traffic Psychological Examination: Conceptualization and Design Proposition

et al. 2021

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“…Pupillometry, however, carries complications when tasks are complex and occur over time frames longer than a single mental operation. After reviewing how we addressed these complications based on work we have reported elsewhere, 31 we show how we combine pupillometric and gaze data to examine how students solve chemistry multiple-choice questions of varying complexity and difficulty. Two research questions guide our study:…”

Section: Research Questionsmentioning

confidence: 99%

“…Four of the questions presented to participants were selected for a mixed-methods analysis. 31 Two questions (the most and least difficult, questions 5 and 7 in the original CCI) were selected on the basis of their percent correct, which was considered as a proxy for difficulty (i.e., a lower percent correct correlated to a more difficult question and vice versa). 48 Two additional questions (CCI questions 6 and 9) were selected for analysis on the basis of their visual structure (see Figure 1 for an exemplar).…”

Section: Data Collectionmentioning

confidence: 99%

“…A qualitative analysis was performed to descriptively capture processes participants may have been engaged in while they answered the multiple-choice items. 31 Gaze videos were replayed in the qualitative analysis software NVivo to identify distinct item-solving tasks. These tasks were named "epochs", following the name for short tasks consisting of several gaze events that can be used in fixation-aligned pupillary response averaging.…”

Section: Epochs Codingmentioning

confidence: 99%

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Looking into the Black Box: Using Gaze and Pupillometric Data to Probe How Cognitive Load Changes with Mental Tasks

2019

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When characterizing students’ item-solving strategies, methods such as interviews and think-aloud protocols are often used. However, these measures provide limited information about sub- or preconscious signals and cognitive processes that also affect students’ item-solving strategies and abilities. A growing number of researchers in chemical education research have begun to address this gap by using physiological measurements to assess cognitive load (e.g., heart rate and EEG) and to look at item-solving strategies (e.g., via eye tracking). One physiological measure of cognitive load that has been well-documented in psychology literature is pupil dilation. In this study, two streams of eye-tracking data (gaze and pupillometric data) were combined to reveal information about what mental tasks general chemistry students were engaged in as they answered Chemical Concepts Inventory (CCI) questions (gaze stream) and how those mental tasks elicited changing levels of cognitive load (pupillometric stream). We found that, for complex multiple-choice tasks, pupil dilation fluctuated throughout the course of solving the item. For a more straightforward true/false task, there was a marked difference in pupil signal between participants who correctly answered the question and those who incorrectly answered it. Those who correctly answered the question had linearly increasing pupillary signals, whereas those who incorrectly answered had pupil signals that more closely resembled those observed during the multiple-choice tasks. Interpretations of these differences are supported using retrospective interviews and previously published literature about CCI items.

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The Impact of Students’ Educational Background, Formal Reasoning, Visualisation Abilities, and Perception of Difficulty on Eye-Tracking Measures When Solving a Context-Based Problem with Submicroscopic Representation

Pavlin

Slapničar

2021

Applying Bio-Measurements Methodologies in Science Education Research

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Beyond Gaze Data: Pupillometry as an Additional Data Source in Eye Tracking

Cited by 6 publications

References 57 publications

HMD-Based VR Tool for Traffic Psychological Examination: Conceptualization and Design Proposition

HMD-Based VR Tool for Traffic Psychological Examination: Conceptualization and Design Proposition

Looking into the Black Box: Using Gaze and Pupillometric Data to Probe How Cognitive Load Changes with Mental Tasks

The Impact of Students’ Educational Background, Formal Reasoning, Visualisation Abilities, and Perception of Difficulty on Eye-Tracking Measures When Solving a Context-Based Problem with Submicroscopic Representation

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