Eye Movement Metrics Research Articles

Dissociable genetic influences on eye movements during abstract versus naturalistic social scene viewing in infancy

Eye-movement metrics like fixation location and duration are increasingly being used in infancy research. We tested whether fixation durations during meaningful social stimulus viewing involve common or different familial influences than fixation durations during viewing of abstract stimulus. We analysed the duration of fixations, and the allocation of fixations to face and motion, from 536 dizygotic and monozygotic 5-month-old twins in: naturalistic scenes including low- and high-level social features, and abstract scenes only having low-level features. We observed significant genetic influences in both conditions (h2naturalistic = 0.30, 95% confidence interval (CI) 0.14 to 0.44; h2abstract = 0.25, 95% CI 0.09 to 0.39), while shared environmental influences were negligible. Although some genetic influences were shared between the two conditions, unique genetic factors were linked to naturalistic scene viewing, indicating that fixation durations index different phenomena dependent on the context. Heritability for face looking was moderate (h2 = 0.19, 95% CI 0.03 to 0.34), and no familial influences were found for motion looking. Exploratory polygenic score analyses revealed no significant associations with fixation measures. This study underscores the dissociable genetic influences on infants’ visual exploration of abstract versus naturalistic stimuli and the importance of considering context when interpreting eye-tracking data.

The link between eye movements and cognitive function in mild to moderate Alzheimer's disease.

This study investigated the relationship between eye movement parameters and cognitive function in patients with mild to moderate Alzheimer's disease (AD). A total of 80 patients with AD (mild and moderate) and 34 normal controls (NC) participated. Neuropsychological assessments were conducted using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), while eye movements were recorded using eye-tracking technology. Comparisons of neuropsychological scores and eye movement parameters were made across the groups, and partial correlation analysis was performed to examine associations between eye movement metrics and specific cognitive domains. No significant differences were found among the groups in pursuit and fixation tasks. However, in pro-saccade tasks, patients in the moderate AD group exhibited significantly lower accuracy and longer latency compared to those in the mild AD and NC groups. Similarly, in anti-saccade tasks, the moderate AD group showed significantly lower accuracy and error correction rates compared to the other groups. Partial correlation analysis revealed that overall cognitive function was positively associated with the accuracy of pro-saccade and anti-saccade tasks, as well as the error correction rate of anti-saccade tasks, but negatively associated with pro-saccade latency. Further, orientation was negatively correlated with saccade latency and positively correlated with saccade accuracy, while visuospatial skills were positively associated with the accuracy of both saccade and anti-saccade tasks. A positive correlation was also observed between word fluency and both saccade accuracy and error correction rate. These findings indicate that eye movement parameters, particularly those related to saccade and anti-saccade tasks, are associated with various cognitive domains in mild to moderate AD patients. Eye-tracking technology may provide a convenient and non-invasive tool for assessing cognitive function and aiding in the diagnosis and evaluation of AD.

Eye movements in oral reading by primary school students: The relevance of punctuation marks

This study aims to explore the relevance of punctuation marks during oral reading. To achieve this objective, we compared eye movement metrics of two groups of 5th-year students, classified based on the Reading Fluency variable. The fluent reading group (FL) consisted of 27 participants, while 31 participants were in the poor reading fluent group (PF). All participants read three types of text: a simple text with punctuation, a complex text with punctuation and a simple text without punctuation. By analyzing the fixations and saccades, the data suggest that the complexity of the text influences the eye-tracking metrics of the PF group, but not the FL group. On the other hand, the presence of punctuation influence the reading behavior of the FL group, but not the PF group. These findings highlight the influence of punctuation and textual complexity on the dynamics of oral reading and offer valuable insights into how reading fluency is related to text comprehention.

Influence of punishments associated with task outcomes in physical and mental efforts performed by semi-elite soccer players during training tasks

ABSTRACT Punishing application associated with the task outcomes is a familiar strategy used by soccer coaches during training, but it has been mainly remained in the research background. To date, no previous studies have addressed the effects of punishments on soccer players’ physical and mental efforts during on-field training sessions. Voluntarily, 40 semi-elite male soccer players from two Spanish teams of the same club participated in the study (M age = 22.90 yrs, SD = 5.60 yrs), performing two training sessions with the same tasks, but different in the use or non-use of punishments associated with the task outcomes. Physical load was registered using Polar Team and Ratio of Perceived Exertion. Mental load was estimated by the NASA-Task Load Index and mental fatigue was collected using a Visual Analogue Scale. A portable eye tracker was used to seek the effects of punishment manipulation on ocular metrics. After training, players achieved higher values of peak and mean heart rate, peak and mean speed, distance/minute, and number of sprints at the session with punishments, compared to the session without them. The punishments also influenced participants’ eye movement metrics because changes were found in pupil diameter, latency and velocity of saccades, and number of saccades and blinks when compared to the two training sessions. However, no differences were found between sessions for subjective mental load and fatigue variables. These findings have practical implications to the design of soccer training tasks because this emotional constraint influenced the physical load and objective mental load of the soccer players, but not their subjective measures of mental load and fatigue.

Skip-AttSeqNet: Leveraging skip connection and attention-driven Seq2seq model to enhance eye movement event detection in Parkinson’s disease

To address the limitations of traditional algorithms in detecting eye movement events, particularly in Parkinson’s disease (PD) patients, this study introduces Skip-AttSeqNet. It presents an innovative approach combining skip-connected, one-dimensional convolutional neural networks with an attention-enhanced, bidirectional long short-term memory network. This hybrid architecture significantly advances smooth pursuit (SP) event detection, as evidenced by its performance on both the GazeCom dataset and a unique dataset of PD patient eye movements. Key innovations in this work include the utilization of skip connections and attention mechanisms, along with optimized training–validation set division, collectively enhancing the model’s accuracy while mitigating overfitting. Skip-AttSeqNet outperforms existing algorithms, achieving a 3.2% higher sample-level F1 score and a notable 6.2% increase in event-level F1 scores for SP detection. Furthermore, we established a smooth-pursuit experimental paradigm and identified significant differences in saccade and SP features between PD patients and healthy older adults through statistical analysis using the Mann–Whitney test. These findings underscore the potential of eye movement metrics as biomarkers for PD, thereby not only strengthening PD diagnosis but also enriching the intersection of computer vision and biomedical research domains.

Visual Attention Distribution of Pilot Flying vs. Pilot Monitoring During Different Flight Phases

With the continuous maturation of technology and the deepening of human-centered design philosophy, eye tracking technology has gradually been applied in research studies for the optimization of flight deck design in commercial aviation. While these studies have focused solely on Pilot Flying (PF), without considering the visual attention distribution of Pilot Monitoring (PM). The purpose of this study was to analyze and compare the visual attention distribution of PF and PM during different flight phases, providing more comprehensive guidance and optimization suggestion to the flight deck design in commercial aviation. This study was conducted in the A320 full-motion flight simulator, with eye tracking technology recording eye movements of PF and PM in the same flight crew simultaneously. The result showed significant differences in three eye movement metrics between PF and PM, not only throughout the whole common manual circuit but also within specific flight phases. Additionally, the results indicated that in certain flight phases, PF and PM exhibited statistically significant correlations in certain eye movement metrics for specific areas of the flight deck. However, in most other instances, no statistically significant correlations were observed between the eye movement metrics of PF and PM. Therefore, the future design of flight decks may benefit from considering differentiation between PF and PM sides in certain flight phases or areas. Additionally, it can be beneficial to make dynamic adjustments to the current flight deck display and control interface while maintaining the existing layout design.

Age-Based Developmental Biomarkers in Eye Movements: A Retrospective Analysis Using Machine Learning.

This study aimed to identify when and how eye movements change across the human lifespan to benchmark developmental biomarkers. The sample size comprised 45,696 participants, ranging in age from 6 to 80 years old (M = 30.39; SD = 17.46). Participants completed six eye movement tests: Circular Smooth Pursuit, Horizontal Smooth Pursuit, Vertical Smooth Pursuit, Horizontal Saccades, Vertical Saccades, and Fixation Stability. These tests examined all four major eye movements (fixations, saccades, pursuits, and vergence) using 89 eye-tracking algorithms. A semi-supervised, self-training, machine learning classifier was used to group the data into age ranges. This classifier resulted in 12 age groups: 6-7, 8-11, 12-14, 15-25, 26-31, 32-38, 39-45, 46-53, 54-60, 61-68, 69-76, and 77-80 years. To provide a descriptive indication of the strength of the self-training classifier, a series of multiple analyses of variance (MANOVA) were conducted on the multivariate effect of the age groups by test set. Each MANOVA revealed a significant multivariate effect on age groups (p < 0.001). Developmental changes in eye movements across age categories were identified. Specifically, similarities were observed between very young and elderly individuals. Middle-aged individuals (30s) generally showed the best eye movement metrics. Clinicians and researchers may use the findings from this study to inform decision-making on patients' health and wellness and guide effective research methodologies.

SARS-CoV-2 Infection Impairs Oculomotor Functions: A Longitudinal Eye-tracking Study.

Although Severe Acute Respiratory Syndrome Coronavirus 2 infection (SARS-CoV-2) is primarily recognized as a respiratory disease, mounting evidence suggests that it may lead to neurological and cognitive impairments. The current study used three eye-tracking tasks (free-viewing, fixation, and smooth pursuit) to assess the oculomotor functions of mild infected cases over six months with symptomatic SARS-CoV-2 infected volunteers. Fifty symptomatic SARS-CoV-2 infected, and 24 self-reported healthy controls completed the eye-tracking tasks in an initial assessment. Then, 45, and 40 symptomatic SARS-CoV-2 infected completed the tasks at 2- and 6-months post-infection, respectively. In the initial assessment, symptomatic SARS-CoV-2 infected exhibited impairments in diverse eye movement metrics. Over the six months following infection, the infected reported overall improvement in health condition, except for self-perceived mental health. The eye movement patterns in the free-viewing task shifted toward a more focal processing mode and there was no significant improvement in fixation stability among the infected. A linear discriminant analysis shows that eye movement metrics could differentiate the infected from healthy controls with an accuracy of approximately 62%, even 6 months post-infection. These findings suggest that symptomatic SARSCoV- 2 infection may result in persistent impairments in oculomotor functions, and the employment of eye-tracking technology can offer valuable insights into both the immediate and long-term effects of SARS-CoV-2 infections. Future studies should employ a more balanced research design and leverage advanced machine-learning methods to comprehensively investigate the impact of SARSCoV- 2 infection on oculomotor functions.

Dyslexia Analysis and Diagnosis Based on Eye Movement.

Dyslexia is a complex reading disorder characterized by difficulties in accurate or fluent word recognition, poor spelling, and decoding abilities. These challenges are not due to intellectual, visual, or auditory deficits. The diagnosis of dyslexia is further complicated by symptom variability, influenced by cultural and personal factors. This study leverages Virtual Reality (VR) advancements, eye movement tracking, and machine learning to create a virtual reading environment that captures eye movement data. This data extracts features such as eye movement metrics, word vectors, and saliency maps. We introduce a novel fusion model that integrates various machine learning algorithms to objectively and automatically assess dyslexia using physiological data derived from user interactions. Our findings suggest that this model significantly enhances the accuracy and efficiency of dyslexia diagnosis, marking an important advancement in educational technology and providing robust support for individuals with dyslexia. Although the sample size was limited to 10 dyslexic and 4 control participants, the results offer valuable insights and lay the groundwork for future studies with larger cohorts.

Impaired orienting function detected through eye movements in patients with temporal lobe epilepsy.

Patients with temporal lobe epilepsy (TLE) often exhibit attention function impairment. The orienting network is the subsystem of the attention network that has not been fully studied. In this study, we used eye-tracking technology with an attention network test (ANT)-based task to assess the orienting function of TLE patients, aiming to characterize their eye movement patterns. A total of 37 TLE patients and 29 healthy controls (HCs) completed the ANT task based on eye-tracking technology. Orienting function damage was mainly assessed by the ANT orienting effect. Eye movement metrics, such as mean first goal-directed saccade latency (MGSL), total saccades, and saccade amplitudes, were compared between groups. The TLE patients had a significantly lower ANT orienting effect (HC, 54.05 ± 34.05; TLE, 32.29 ± 39.54) and lower eye-tracking orienting effect (HC, 116.98 ± 56.59; TLE, 86.72 ± 59.10) than those of the HCs. The larger orienting effects indicate that orienting responses are faster when receiving a spatial cue compared with a center cue. In the spatial cue condition, compared with HCs, the TLE group showed a longer first goal-directed saccade latency (HC, 76.77 ± 58.87 ms; TLE, 115.14 ± 59.15 ms), more total saccades (HC, 28.46 ± 12.30; TLE, 36.69 ± 15.13), and larger saccade amplitudes (HC, 0.75° ± 0.60°; TLE, 1.36° ± 0.89°). Furthermore, there was a positive correlation of the orienting-effect score between the ANT task and eye-tracking metrics (r = 0.58, p < 0.05). We innovatively developed a new detection method using eye-tracking technology in combination with an ANT-based task to detect the orienting function in TLE patients. The current research demonstrated that TLE patients had a significant orienting dysfunction with a specific saccade pattern characterized by a longer first goal-directed saccade latency, more total saccades, and larger saccade amplitudes. These oculomotor metrics are likely to be a better indicator of orienting function and may potentially be used for behavioral-based interventions and long-term cognition monitoring in TLE patients.

Prediction of Mild Cognitive Impairment using eye movements and other easily accessible measures

AbstractBackgroundThe early identification of patients at risk of dementia and timely medical intervention can be effective in preventing disease progression and mitigate burdens and costs of health insurance. Although the current diagnostic tests for preclinical and prodromal Alzheimer’s disease (AD) using neuropsychological evaluation and biomarkers can accurately predict the progression to AD dementia, the high cost, invasive nature, and limited availability restrict their use to wealthy clinics only. Therefore, we developed a model to predict cognitive impairment based on non‐invasive information, including eye movement (EM) data.MethodEye‐tracking data was extracted from 594 subjects, 428 cognitively normal (CN) controls, and 166 patients with mild cognitive impairment (MCI) while they performed Prosaccade/Antisaccade (PS/AS) and Go/No‐go tasks. EM behavior was compared by task after stratification by cognitive status and controlling for age, sex, and education. We used logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI) from the EM metrics.ResultLogistic regression models suggested increased OR of MCI from EM metrics, including wider latency variability, fixation duration variability, a higher number of errors committed, anticipations, and omissions with 95% CI of OR between 1.213‐1.621.ConclusionEM metric changes linked with MCI are associated with deficits in attentional and executive functions. The models built from non‐invasive data allow the discrimination of patients with MCI from cognitively normal adults. In summary, our results suggest that eye tracking, in combination with demographics and brief cognitive tests, might significantly improve the diagnostic prediction of MCI.

Visual attention predictive model of built colonial heritage based on visual behaviour and subjective evaluation

Although physiological measurements, subjective evaluation and other methods have been applied to visual attention research, architects still lack a systematic quantitative classification method when assessing the visual attention to built colonial heritage. This study aimed to investigate the relationship between people’s visual behaviour and subjective evaluation when observing built colonial heritage and to construct a prediction model based on eye-movement metrics and subjective evaluation indicators to distinguish the visual attention to built colonial heritage. This study recorded data from 54 participants while observing five scenes of built colonial heritage, and the results showed that participants had different visual behaviours and subjective evaluations when viewing built colonial heritage in different scenes. And visual attention to built colonial heritage was negatively correlated with the average saccades peak velocity and average saccades amplitude and positively correlated with the average pupil diameter; visual attention was correlated with 12 subjective evaluation indicators. The eye-movement metrics and subjective evaluation indicators with correlation to visual attention were used as input variables to construct a prediction model of visual attention to built colonial heritage based on the BP neural network. Different built colonial heritage’s low, middle and high visual attention were identified with high accuracy (74.46%). This quantitative method can help architects to measure the visual attention to built colonial heritage to develop conservation and renewal strategies.

Distraction and visual search characteristics of young drivers when using navigation system displays

Navigation systems are fast and efficient sources of road information for drivers. However, they can increase the potential for accidents by distracting drivers. This study investigated the impact of navigation systems on driver distraction and visual search under various driving conditions. Using a driving simulator, eye-tracking technology recorded visual search data from twenty young drivers. The experiment analyzed factors such as driving environment (urban and rural), illumination level (day and night), and navigation system display size (large and small), as well as their interactions. Multiple eye movement metrics were employed, including duration and frequency of GPS fixation, dwell duration on the road ahead, and dwelling on mirrors and side windows. Statistical analysis employed repeated measures ANOVA to analyze the data. Findings revealed that small GPS displays caused greater distraction in terms of average and total gaze duration. Additionally, distraction increased during daytime driving conditions. In terms of visual search, wider and more dispersed search patterns were observed during the day, resulting in improved driving performance. This study aims to compare small and large navigation displays to identify the more effective option in reducing driver distractions. The research contributes to understanding driver distraction and visual search when using navigation system displays.

Saccadic eye movement variables as biomarkers for cognitive decline in elderly individuals.

Alzheimer's disease (AD) is the leading cause of Dementia, and mild cognitive impairment (MCI) is often considered a precursor to the development of AD dementia and other types of Dementia. Biomarkers such as amyloid beta are specific and sensitive in identifying AD and can identify individuals who have biological evidence of the disease but have no symptoms, but clinicians and researchers may not easily use them on a large scale. Ocular biomarkers, such as those obtained through eye tracking (ET) technology, have the potential as a diagnostic tool due to their accuracy, affordability, and ease of use. In this study, we show that eye movement (EM) metrics from an interleaved Pro/Anti-saccade (PS/AS) ET task can differentiate between cognitively normal (CN) and MCI subjects and that the presence of Aβ brain deposits, a biomarker of AD, significantly affects performance on these tasks. Individuals with Aβ deposits (Aβ+) performed worse than those without (Aβ-). Our findings suggest that eye-tracking measurements may be a valuable tool for detecting amyloid brain pathology and monitoring changes in cognitive function in CN and MCI individuals over time.Clinical Relevance- The PS/AS paradigm, which measures saccadic eye movements, can accurately detect subtle cognitive impairments and changes in the brain associated with Alzheimer's disease in CN and MCI individuals. This makes it a valuable tool for identifying individuals at risk for cognitive decline and tracking changes in cognitive function over time.

Eye movement changes as an indicator of mild cognitive impairment.

Early identification of patients at risk of dementia, alongside timely medical intervention, can prevent disease progression. Despite their potential clinical utility, the application of diagnostic tools, such as neuropsychological assessments and neuroimaging biomarkers, is hindered by their high cost and time-consuming administration, rendering them impractical for widespread implementation in the general population. We aimed to develop non-invasive and cost-effective classification models for predicting mild cognitive impairment (MCI) using eye movement (EM) data. We collected eye-tracking (ET) data from 594 subjects, 428 cognitively normal controls, and 166 patients with MCI while they performed prosaccade/antisaccade and go/no-go tasks. Logistic regression (LR) was used to calculate the EM metrics' odds ratios (ORs). We then used machine learning models to construct classification models using EM metrics, demographic characteristics, and brief cognitive screening test scores. Model performance was evaluated based on the area under the receiver operating characteristic curve (AUROC). LR models revealed that several EM metrics are significantly associated with increased odds of MCI, with odds ratios ranging from 1.213 to 1.621. The AUROC scores for models utilizing demographic information and either EM metrics or MMSE were 0.752 and 0.767, respectively. Combining all features, including demographic, MMSE, and EM, notably resulted in the best-performing model, which achieved an AUROC of 0.840. Changes in EM metrics linked with MCI are associated with attentional and executive function deficits. EM metrics combined with demographics and cognitive test scores enhance MCI prediction, making it a non-invasive, cost-effective method to identify early stages of cognitive decline.

An investigation of feed-forward and feedback eye movement training in immersive virtual reality.

The control of eye gaze is critical to the execution of many skills. The observation that task experts in many domains exhibit more efficient control of eye gaze than novices has led to the development of gaze training interventions that teach these behaviours. We aimed to extend this literature by i) examining the relative benefits of feed-forward (observing an expert's eye movements) versus feed-back (observing your own eye movements) training, and ii) automating this training within virtual reality. Serving personnel from the British Army and Royal Navy were randomised to either feed-forward or feed-back training within a virtual reality simulation of a room search and clearance task. Eye movement metrics - including visual search, saccade direction, and entropy - were recorded to quantify the efficiency of visual search behaviours. Feed-forward and feed-back eye movement training produced distinct learning benefits, but both accelerated the development of efficient gaze behaviours. However, we found no evidence that these more efficient search behaviours transferred to better decision making in the room clearance task. Our results suggest integrating eye movement training principles within virtual reality training simulations may be effective, but further work is needed to understand the learning mechanisms.

Studying Developer Eye Movements to Measure Cognitive Workload and Visual Effort for Expertise Assessment

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.

Landscape Design Intensity and Its Associated Complexity of Forest Landscapes in Relation to Preference and Eye Movements

Understanding how people perceive landscapes is essential for the design of forest landscapes. The study investigates how design intensity affects landscape complexity, preference, and eye movements for urban forest settings. Eight groups of twenty-four pictures, representing lawn, path, and waterscape settings in urban forests, with each type of setting having two groups of pictures and one group having four pictures, were selected. The four pictures in each group were classified into slight, low, medium, and high design intensities. A total of 76 students were randomly assigned to observe one group of pictures within each type of landscape with an eye-tracking apparatus and give ratings of complexity and preference. The results indicate that design intensity was positively associated with subjective landscape complexity but was positively or negatively related to objective landscape complexity in three types of settings. Subjective landscape complexity was found to significantly contribute to visual preference across landscape types, while objective landscape complexity did not contribute to preference. In addition, the marginal effect of medium design intensity on preference was greater than that of low and high design intensity in most cases. Moreover, although some eye movement metrics were significantly related to preference in lawn settings, none were found to be indicative predictors for preference. The findings enrich research in visual preference and assist landscape designers during the design process to effectively arrange landscape design intensity in urban forests.

Eye movement characteristics in a mental rotation task presented in virtual reality.

Eye-tracking technology provides a reliable and cost-effective approach to characterize mental representation according to specific patterns. Mental rotation tasks, referring to the mental representation and transformation of visual information, have been widely used to examine visuospatial ability. In these tasks, participants visually perceive three-dimensional (3D) objects and mentally rotate them until they identify whether the paired objects are identical or mirrored. In most studies, 3D objects are presented using two-dimensional (2D) images on a computer screen. Currently, visual neuroscience tends to investigate visual behavior responding to naturalistic stimuli rather than image stimuli. Virtual reality (VR) is an emerging technology used to provide naturalistic stimuli, allowing the investigation of behavioral features in an immersive environment similar to the real world. However, mental rotation tasks using 3D objects in immersive VR have been rarely reported. Here, we designed a VR mental rotation task using 3D stimuli presented in a head-mounted display (HMD). An eye tracker incorporated into the HMD was used to examine eye movement characteristics during the task synchronically. The stimuli were virtual paired objects oriented at specific angular disparities (0, 60, 120, and 180°). We recruited thirty-three participants who were required to determine whether the paired 3D objects were identical or mirrored. Behavioral results demonstrated that the response times when comparing mirrored objects were longer than identical objects. Eye-movement results showed that the percent fixation time, the number of within-object fixations, and the number of saccades for the mirrored objects were significantly lower than that for the identical objects, providing further explanations for the behavioral results. In the present work, we examined behavioral and eye movement characteristics during a VR mental rotation task using 3D stimuli. Significant differences were observed in response times and eye movement metrics between identical and mirrored objects. The eye movement data provided further explanation for the behavioral results in the VR mental rotation task.

Webcam-based eye-tracking to measure visual expertise of medical students during online histology training.

Visual expertise is essential for image-based tasks that rely on visual cues, such as in radiology or histology. Studies suggest that eye movements are related to visual expertise and can be measured by near-infrared eye-tracking. With the popularity of device-embedded webcam eye-tracking technology, cost-effective use in educational contexts has recently become amenable. This study investigated the feasibility of such methodology in a curricular online-only histology course during the 2021 summer term. At two timepoints (t1 and t2), third-semester medical students were asked to diagnose a series of histological slides while their eye movements were recorded. Students' eye metrics, performance and behavioral measures were analyzed using variance analyses and multiple regression models. First, webcam-eye tracking provided eye movement data with satisfactory quality (mean accuracy=115.7 px±31.1). Second, the eye movement metrics reflected the students' proficiency in finding relevant image sections (fixation count on relevant areas=6.96±1.56 vs. irrelevant areas=4.50±1.25). Third, students' eye movement metrics successfully predicted their performance (R2adj=0.39, p<0.001). This study supports the use of webcam-eye-tracking expanding the range of educational tools available in the (digital) classroom. As the students' interest in using the webcam eye-tracking was high, possible areas of implementation will be discussed.