Research in Progress: Investigating the Intersections of Attention and Self-Regulated Learning through Stimulated Recall and Student’s Eye-Tracking Behaviour

Introduction: After a stroke, individuals commonly experience visual problems and impaired cognitive function, which can significantly impact their daily lives. In addition to visual neglect and hemianopia, stroke survivors often have difficulties with visual search tasks. Researchers are increasingly interested in using eye tracking technology to study cognitive processing and determine whether eye tracking metrics can be used to screen and assess cognitive impairment in patients with neurological disorders. As such, assessing these areas and understanding their relationship is crucial for effective stroke rehabilitation. Methods: We enrolled 60 stroke patients in this study and evaluated their eye tracking performance and cognitive function through a series of tests. Subsequently, we divided the subjects into two groups based on their scores on the HK-MoCA test, with scores below 21 out of 30 indicating cognitive impairment. We then compared the eye tracking metrics between the two groups and identified any significant differences that existed. Spearman correlation analysis was conducted to explore the relationship between clinical test scores and eye tracking metrics. Moreover, we employed a Mann-Whitney U test to compare eye tracking metrics between groups with and without cognitive impairment. Results: Our results revealed significant correlations between various eye tracking metrics and cognitive tests (p ≤ 0.001–0.041). Furthermore, the group without cognitive impairment demonstrated higher saccade velocity, gaze path velocity, and shorter time to target than the group with cognitive impairment (p ≤ 0.001–0.040). Receiver operating characteristic curve analyses were performed, and the optimal cut-off values for gaze path velocity and saccade velocity were 329.665 (px/s) (sensitivity = 0.80, specificity = 0.533) and 2.150 (px/ms) (sensitivity = 0.733, specificity = 0.633), respectively. Conclusions: Our findings indicate a significant correlation between eye tracking metrics and cognitive test scores. Furthermore, the group with cognitive impairment exhibited a significant difference in these metrics, and a cut-off value was identified to predict whether a client was experiencing cognitive impairment.

Advanced upper limb prostheses aim to restore coordinated hand and arm function. However, this objective can be difficult to quantify as coordinated movements require an intact visuomotor system. Eye tracking has recently been applied to study the visuomotor behaviours of upper limb prosthesis users by enabling the calculation of eye movement metrics. This scoping review aims to characterize the visuomotor behaviours of upper limb prosthesis users as described by eye tracking metrics, to summarize the eye tracking metrics used to describe prosthetic behaviour, and to identify gaps in the literature and potential areas for future research. A review of the literature was performed to identify articles that reported eye tracking metrics to evaluate the visual behaviours of individuals using an upper limb prosthesis. Data on the level of amputation, type of prosthetic device, type of eye tracker, primary eye metrics, secondary outcome metrics, experimental task, aims, and key findings were extracted. Seventeen studies were included in this scoping review. A consistently reported finding is that prosthesis users have a characteristic visuomotor behaviour that differs from that of individuals with intact arm function. Visual attention has been reported to be directed more towards the hand and less towards the target during object manipulation tasks. A gaze switching strategy and delay to disengage gaze from the current target has also been reported. Differences in the type of prosthetic device and experimental task have revealed some distinct gaze behaviours. Control factors have been shown to be related to gaze behaviour, while sensory feedback and training interventions have been demonstrated to reduce the visual attention associated with prosthesis use. Eye tracking metrics have also been used to assess the cognitive load and sense of agency of prosthesis users. Overall, there is evidence that eye tracking is an effective tool to quantitatively assess the visuomotor behaviour of prosthesis users and the recorded eye metrics are sensitive to change in response to various factors. Additional studies are needed to validate the eye metrics used to assess cognitive load and sense of agency in upper limb prosthesis users.

Eye tracking assessments that include pupil metrics can supplement current clinical assessments of vision and autonomic dysfunction in concussed adolescents. This study aimed to explore the utility of a 220-second eye tracking assessment in distinguishing eye position, saccadic movement, and pupillary dynamics among uninjured adolescents, those with acute post-concussion symptoms (≤28 days since concussion), or those with persistent post-concussion symptoms (>28 days since concussion). Two hundred fifty-six eye tracking metrics across a prospective observational cohort of 180 uninjured adolescents recruited from a private suburban high school and 224 concussed adolescents, with acute or persistent symptoms, recruited from a tertiary care subspecialty concussion care program, 13 to 17 years old, from August 2017 to June 2021 were compared. Kruskal-Wallis tests were used, and Bonferroni corrections were applied to account for multiple comparisons and constructed receiver operating characteristic curves. Principal components analysis and regression models were applied to determine whether eye tracking metrics can augment clinical and demographic information in differentiating uninjured controls from concussed adolescents. Two metrics of eye position were worse in those with concussion than uninjured adolescents, and only one metric was significantly different between acute cases and persistent cases. Concussed adolescents had larger left and right mean, median, minimum, and maximum pupil size than uninjured controls. Concussed adolescents had greater differences in mean, median, and variance of left and right pupil size. Twelve metrics distinguished female concussed participants from uninjured; only four were associated with concussion status in males. A logistic regression model including clinical and demographics data and transformed eye tracking metrics performed better in predicting concussion status than clinical and demographics data alone. Objective eye tracking technology is capable of quickly identifying vision and pupillary disturbances after concussion, augmenting traditional clinical concussion assessments. These metrics may add to existing clinical practice for monitoring recovery in a heterogeneous adolescent concussion population.

Display clutter is a problem that affects operators in various data-rich environments. Clutter measurement techniques such as image processing and performance measures can provide an estimate of clutter but are largely not suited to tracing the effects of clutter on the dynamic allocation of attention. Eye tracking is a promising process-oriented tool that can help assess in real-time the attentional costs associated with the different aspects of clutter. In this experiment, we investigated which of a number of eye tracking metrics in the literature are sensitive to clutter. Twenty-two participants were asked to look for a target in static and dynamic images that were classified as either high or low in clutter. Response time and error rate were recorded, and an eye tracker was used to compute the identified eye tracking metrics. Results showed that, in both the static and dynamic conditions, a large number of eye tracking metrics were significantly affected by an increase in clutter. This suggests that eye tracking can be used to supplement other clutter measurement techniques by providing information about dynamic attention allocation.

Robotic-assisted surgery (RAS) is one of the most significant advancements in surgical techniques in the past three decades. It provides benefits of reduced infection risks and shortened recovery time over open surgery as well as improved dexterity, stereoscopic vision, and ergonomic console over laparoscopic surgery. The prevalence of RAS systems has increased over years and is expected to grow even larger. However, the major concerns of RAS are the technical difficulty and the system complexity, which can result in long learning time and impose extra cognitive workload and stress on the operating room. Human Factor and Ergonomics (HFE) perspective is critical to patient safety and relevant researches have long provided methods to improve surgical outcomes. Yet, limited studies especially using objective measurements, have been done in the RAS environment. With advances in wearable sensing technology and data analytics, the applications of physiological measures in HFE have been ever increasing. Physiological measures are objective and real-time, free of some main limitations in subjective measures. Eye tracker as a minimally-intrusive and continuous measuring device can provide both physiological and behavioral metrics. These metrics have been found sensitive to changes in workload in various domains. Meanwhile, electroencephalography (EEG) signals capture electrical activity in the cerebral cortex and can reflect cognitive processes that are difficult to assess with other objective measures. Both techniques have the potential to help address some of the challenges in RAS. In this study, eight RAS trainees participated in a 3-month long experiment. In total, they completed 26 robotic skills simulation sessions. In each session, participants performed up to 12 simulated RAS exercises with varying levels of difficulty. For Research Question I, correlation and mixed effect analyses were conducted to explore the relationships between eye tracking metrics and workload. Machine learning classifiers were used to determine the sensitivity of differentiating low and high workload with eye tracking metrics. For Research Question II, two eye tracking metrics and one EEG metric were used to explain participants’ performance changes between consecutive sessions. Correlation and ANOVA analyses were conducted to examine whether variations in performance had significant relationships with variations in objective metrics. Classification models were built to examine the capability of objective metrics in predicting improvement during RAS training. In Research Question I, pupil diameter and gaze entropy distinguished between different task difficulty levels, and both metrics increased as the level of difficulty increased. Yet only gaze entropy was correlated with subjective workload measurement. The classification model achieved an average accuracy of 89.3% in predicting workload levels. In Research Question II, variations in gaze entropy and engagement index were negatively correlated with variations in task performance. Both metrics tended to decrease when performance increased. The classification model achieved an average accuracy of 68.5% in predicting improvements. Eye tracking metrics can measure both task workload and perceived workload during simulated RAS training. It can potentially be used for real-time monitoring of workload in RAS procedure to identify task contributors to high workload and provide insights for training. When combined with EEG, the objective metrics can explain the performance changes during RAS training, and help estimate room for improvements.

ObjectiveWe conducted a literature review investigating the validity of eye tracking metrics appropriately representing trust in automation.BackgroundAs researchers grow interested in measuring trust in automation, there has been a need to find a reliable and accurate measurement tool. Many articles have measured automation trust using eye tracking, assuming that as trust increases, visual attention from eye tracking metrics decreases. Eye tracking is an attractive potential measure for its nonintrusive and objective nature.MethodIn this systematic literature review, we looked at studies that have tested the relationship between eye tracking and trust to determine its validity and reliability.ResultsAcross 22 articles that investigated the relationship between trust and eye tracking, only about half found a negative significant relationship, whereas the other half found no relationship at all.ConclusionThe relationship between automation trust and eye tracking is inconsistent and unreliable. A wide variety of trust and eye tracking metrics were used, but only about half of the papers found any kind of relationship. The relationship did not appear robust enough to prevail when different eye tracking and trust metrics were applied in various study designs.ApplicationAn effective eye tracking-trust relationship would be useful in various applications (e.g., autonomous driving). Further, this relationship is crucial when there is a clear distinction between attention allocated to automated components of a system (e.g., car display) and unrelated displays to allow for an easy separation of a location associated with high trust versus low trust.

ObjectiveThe study aims to validate eye movement tracking performed without a baseline study as a biomarker for concussion in a paediatric population.DesignThis is a cross-sectional case control study of patients diagnosed with concussion in a referral centre compared to non-concussed controls.MethodsEye movements were recorded with an SR Research Eyelink 1000 eye tracker while a 220-second video was played. Eye tracking metrics were compared to Acute Concussion Evaluation (ACE) scores and clinical assessments of convergence and accommodation.Results56 children with concussions (mean age of 13 years), as defined by symptom presence following an impulsive injury to the brain were evaluated at a mean of 22 weeks post-injury. Twelve eye tracking metrics were significantly different between concussed children and 83 uninjured controls. A model built on a balanced sub-sample to classify concussion based on eye tracking achieved an AUC of 0.854 (sensitivity 71.9%; specificity 84.4%). Two metrics were significant predictors of abnormal near point convergence (NPC) and accommodation. The model built to classify concussion based on NPC status achieved a specificity of 95.8% and a sensitivity of 57.1%. Reduced binocular amplitude of accommodation had a spearman correlation of 0.752 (p-value<0.001) with NPC. Seven eye tracking metrics were found to have a strong correlation (R=0.781) with binocular amplitude of accommodation.ConclusionsEye tracking reliably detected concussion and convergence and accommodative abnormalities in the paediatric population. We propose that eye tracking without baseline assessment may serve as an objective measure of concussion in paediatric patients.Competing interestsUzma Samadani has submitted intellectual property describing the technology utilised in this paper.These patents are owned by NYU, the VA and HCMC and licensed to Oculogica Inc., a company in which all of the above parties have an equity interest

Eye tracking metrics provide information about cognitive function and basic oculomotor characteristics. There have been many studies analyzing eye tracking signals using different algorithms. However, these algorithms generally are based on the initial setting parameter. This might cause the subjective interpretation of eye tracking analysis. The main aim of this study was to develop a data-driven algorithm to detect fixations and saccades without any subjective settings. Three subjects were included in this study. Eye tracking signal was acquired with the VIVE Pro Eye in virtual reality (VR) environment while subjects were reading a paragraph. The algorithms based on the calculation of threshold were employed to calculate eye metrics including total fixation duration, total fixation number, total saccades number and average pupil diameter. The proposed algorithm, which is based on calculating the initial threshold, based on mean, and standard deviation of eye tracking signal within experiment duration, gave the same results obtained adaptive filtering reported in literature (average fixation duration for three subjects= 11515 ms ± 6951.2, average fixation count for three subjects= 17.33 ± 4.16). On the other hand, our proposed algorithm didn’t use any certain objective parameter as like adaptive filtering. As a conclusion, VIVE Pro Eye may be utilized as an eye movement assessment device, and, the suggested approach might be utilized to analyze objective eye tracking metrics.

Eye tracking metrics of orthopedic surgeons with different competency levels who practice simulation-based hip arthroscopic procedures

Display clutter causes decrements in visual search performance and can be a threat to safety and efficiency in complex, data-rich domains. Addressing the problem requires a means to detect the presence of clutter in real time, predict its effects, and then trigger countermeasures before breakdowns in information search can occur. Eye tracking is a promising technique for achieving these goals; however, to date, it has been used almost exclusively offline for display evaluation purposes. The goal of this research was instead to develop and evaluate models that combine eye tracking metrics to detect the effects of clutter early on in the search process. Participants were asked to locate targets in a simulated graphics program. Three eye tracking metrics—scanpath length, mean saccade amplitude, and mean fixation duration—were calculated over a 3-second time window. These metrics were then used as input to a set of logistic regression models to predict whether users’ response time will be relatively long or short. The accuracy of the models averaged 75% and the true positive rate was above 90%, with an ability to predict response time as early as 3.6 s into the visual search task. The results of this study confirm that eye tracking metrics can be used to predict the effects of display clutter in real time. They add to the knowledge base in attention and eye tracking, and they ultimately contribute to the design of adaptive displays that lead to improved operator performance.

The objective was to use eye tracking to trace the underlying changes in attention allocation associated with the performance effects of clutter, stress, and task difficulty in visual search and noticing tasks. Clutter can degrade performance in complex domains, yet more needs to be known about the associated changes in attention allocation, particularly in the presence of stress and for different tasks. Frequently used and relatively simple eye tracking metrics do not effectively capture the various effects of clutter, which is critical for comprehensively analyzing clutter and developing targeted, real-time countermeasures. Electronic medical records (EMRs) were chosen as the application domain for this research. Clutter, stress, and task difficulty were manipulated, and physicians' performance on search and noticing tasks was recorded. Several eye tracking metrics were used to trace attention allocation throughout those tasks, and subjective data were gathered via a debriefing questionnaire. Clutter degraded performance in terms of response time and noticing accuracy. These decrements were largely accentuated by high stress and task difficulty. Eye tracking revealed the underlying attentional mechanisms, and several display-independent metrics were shown to be significant indicators of the effects of clutter. Eye tracking provides a promising means to understand in detail (offline) and prevent (in real time) major performance breakdowns due to clutter. Display designers need to be aware of the risks of clutter in EMRs and other complex displays and can use the identified eye tracking metrics to evaluate and/or adjust their display.

Flight decks of the future are being enhanced through improved avionics that adapt to both aircraft and operator state. Eye tracking allows for non-invasive analysis of pilot eye movements, from which a set of metrics can be derived to effectively and reliably characterize workload. This research identifies eye tracking metrics that correlate to aircraft automation conditions, and identifies the correlation of pilot workload to the same automation conditions. Saccade length was used as an indirect index of pilot workload: Pilots in the fully automated condition were observed to have on average, larger saccadic movements in contrast to the guidance and manual flight conditions. The data set itself also provides a general model of human eye movement behavior and so ostensibly visual attention distribution in the cockpit for approach to land tasks with various levels of automation, by means of the same metrics used for workload algorithm development.

High mental workload, in addition to changes in workload, can negatively affect operators, but it is not clear how sudden versus gradual workload transitions influence performance and visual attention allocation. This knowledge is important as sudden shifts in workload are common in multitasking domains. The objective of this study was to investigate, using performance and eye tracking metrics, how constant versus variable levels of workload affect operators in the context of a dual-task paradigm. An unmanned aerial vehicle command and control simulation varied task load between low, high, gradually transitioning from low to high, and suddenly transitioning from low to high. Performance on a primary and secondary task and several eye tracking measures were calculated. There was no significant difference between sudden and gradual workload transitions in terms of performance or attention allocation overall; however, both sudden and gradual workload transitions changed participants’ strategy in dealing with the primary and secondary task as compared to low/high workload. Also, eye tracking metrics that are not frequently used, such as transition rate and stationary entropy, provided more insight into performance differences. These metrics can potentially be used to better understand operators’ strategies and could form the basis of an adaptive display.

To explore the utility of an eye-tracking assessment in distinguishing binocular alignment, saccadic movement, and pupillary dynamics among uninjured adolescents, acute cases (= 28 days since concussion), and persistent cases (>28 days since concussion). Visual and autonomic system disturbances are common sequelae of concussion. Quantification of visual and autonomic dysfunction via an eye tracking device could provide an objective method of acute diagnosis and subacute identification of ongoing injury. We compared 347 eye tracking metrics, derived from a 220 seconds eye-tracking assessment, among 132 uninjured adolescents (mean age: 15.3, 56.2% female), 110 acute cases (mean days since injury: 12.5, mean age: 15.4, 46.4% female), and 95 persistent cases (mean days since injury: 53.6, mean age: 15.4, 70.2% female) using Kruskal-Wallis tests with Bonferroni corrections to account for multiple comparisons. Nine eye-tracking metrics were significantly associated with injury status. One measure of binocular alignment (acute v. control: p = 0.003, persistent v. control: p = 0.001) and one measure of saccadic movement (acute v. persistent: p = 0.03, acute v. control: p = 0.03, persistent v. control: p < 0.001) were worse in cases. Cases had larger left and right mean and median pupil size than uninjured adolescents (acute v. control, p < 0.001; persistent v. control, p < 0.001). Cases had greater differences in mean (acute v. control: p < 0.001, persistent v. control: p < 0.001), median (acute v. control, p < 0.001, persistent v. control, p = 0.003), and variance of (acute v. control: p < 0.001, persistent v. control: p < 0.001) left and right pupil size. Eight of these metrics distinguished female cases from uninjured adolescents, but similar differences were not observed in male participants. Objective eye tracking technology can identify vision and pupillary disturbances after concussion. These metrics could be integrated into clinical practice to monitor recovery in a heterogeneous adolescent concussion population and may identify sex-specific differences in autonomic dysfunction.

Eye movements have been widely used to investigate cognitive processes during first language (L1) reading and in the last few years it has become more common for applied linguists to use eye tracking technology to examine topics that had previously been investigated using off-line measures (Conklin & Pellicer-Sanchez, 2016). However, few eye movement studies have investigated Arabic L1 speakers reading in English, although there have been numerous studies which showed that this population experiences great difficulty learning to read in English (see, for example, Abu-Rabia, 1997b; Fender, 2003, 2008; Hayes-Harb, 2006;; Randall, 2007; Randall & Groom, 2009; Randall & Meara, 1988; Ryan, 1997; Ryan & Meara, 1991; Saigh & Schmitt, 2012; Thompson-Panos & Thomas-Ruzic, 1983). There is general consensus in the literature that these problems are related to inefficient processing of English vowels. The overall aim of this thesis was to investigate the causes of the reading difficulties I observed with my own students and then to devise a barrage of pedagogical interventions which would remediate these problems. The research was comprised of two studies. The aim of Study One of the present research was to investigate the differences in eye movements between skilled English L1 (N=36) and Arabic L1 EFL participants (N=39) reading English sentences. Study One found that the Arabic L1 participants displayed eye movements which were significantly different from the patterns exhibited by the English L1 participants, and were indicative of potentially less efficient cognitive processes. These differences were demonstrated in 10 of the 11 metrics calculated. Specifically, the Arabic L1 EFL participants exhibited significantly more and longer fixations than the English L1 participants. They also made significantly more and shorter (forward) saccades than the English L1 group. Furthermore, data analysis showed a highly significant difference between the two groups in visits on vowels and consonants. Study One constitutes an important contribution to the literature on the difficulties experienced by Arabic L1 students learning to read in English. It demonstrates that their eye movements are significantly different from those of skilled English L1 readers. Little or no work exists which investigates any differences in allotment of visual attention when comparing the eye movements on vowels and consonants of Arabic L1 and English L1 speakers as they read sentences in English. The finding that the Arabic L1 EFL participants spent more time attending to vowels than did the English L1 participants questions the ‘vowel blindness’ hypothesis as proposed by Ryan and Meara (1991). This refers to the assumption that Arabic L1 speakers “lack an awareness of the function which vowels perform in English” (Ryan, 1997, p. 189) and consequently do not recognize or attend to them.The aim of Study Two was to investigate the effects of focused reading interventions on the eye movement patterns and overall reading proficiency of Arabic L1 EFL students. Study Two was a quasi-experimental study which compared two groups of proficiency-matched Arabic L1 EFL learners (N= 39), before and after an intensive reading intervention programme during a 14-week semester at a technical college in Qatar. It included two intact classes in the experimental group (N=20) which received reading interventions consisting of textual enhancement, phonemic awareness, spelling, tracking exercises, rapid word recognition and oral text fluency and two intact classes in the control group which received regular classroom instruction (N=19). The effect of the treatment on reading test scores was analysed using a 2-way repeated ANOVA. Analysis of total reading scores showed a significant main effect for time, but no significant main effect for experimental condition. To investigate the eye movements of the two groups before and after treatment, this phase of the study used the same eye tracking metrics employed in Study One. Results showed there was no statistically significant interaction between the experimental group and time, indicating that both the treatment and control groups showed improvement in their eye tracking measures during the 14 weeks. Study Two is the first study to investigate a barrage of pedagogical interventions on the eye movements and reading proficiency of Arabic L1 EFL students. Although the interventions did not produce statistically significant results, the study provides a building block for future studies using focused pedagogical interventions with this particular group of learners.