Bern Open Publishing

The intent of this paper is to provide an introduction into the bourgeoning field of eye tracking in Virtual Reality (VR). VR itself is an emerging technology on the consumer market, which will create many new opportunities in research. It offers a lab environment with high immersion and close alignment with reality. An experiment which is using VR takes place in a highly controlled environment and allows for a more in-depth amount of information to be gathered about the actions of a subject. Techniques for eye tracking were introduced more than a century ago and are now an established technique in psychological experiments, yet recent development makes it versatile and affordable. In combination, these two techniques allow unprecedented monitoring and control of human behavior in semi-realistic conditions. This paper will explore the methods and tools which can be applied in the implementation of experiments using eye tracking in VR following the example of one case study. Accompanying the technical descriptions, we present research that displays the effectiveness of the technology and show what kind of results can be obtained when using eye tracking in VR. It is meant to guide the reader through the process of bringing VR in combination with eye tracking into the lab and to inspire ideas for new experiments.

The surprisal of a word on a probabilistic grammar constitutes a promising complexity metric for human sentence comprehension difficulty. Using two different grammar types, surprisal is shown to have an effect on fixation durations and regression probabilities in a sample of German readers’ eye movements, the Potsdam Sentence Corpus. A linear mixed-effects model was used to quantify the effect of surprisal while taking into account unigram frequency and bigram frequency (transitional probability), word length, and empirically-derived word predictability; the socalled “early” and “late” measures of processing difficulty both showed an effect of surprisal. Surprisal is also shown to have a small but statistically non-significant effect on empirically-derived predictability itself. This work thus demonstrates the importance of including parsing costs as a predictor of comprehension difficulty in models of reading, and suggests that a simple identification of syntactic parsing costs with early measures and late measures with durations of post-syntactic events may be difficult to uphold.

Models of eye movement control in reading and their impact on the field are discussed. Differences between the E-Z Reader model and the SWIFT model are reviewed, as are benchmark data that need to be accounted for by any model of eye movement control. Predictions made by the models and how models can sometimes account for counterintuitive findings are also discussed. Finally, the role of models and data in further understanding the reading process is considered.

While many current models of scene perception debate the relative roles of low- and highlevel factors in eye guidance, systematic tendencies in how the eyes move may be informative. We consider how each saccade and fixation is influenced by that which preceded or followed it, during free inspection of images of natural scenes. We find evidence to suggest periods of localized scanning separated by ‘global’ relocations to new regions of the scene. We also find evidence to support the existence of small amplitude ‘corrective’ saccades in natural image viewing. Our data reveal statistical dependencies between successive eye movements, which may be informative in furthering our understanding of eye guidance.

We use simulations to investigate the effect of sampling frequency on common dependent variables in eye-tracking. We identify two large groups of measures that behave differently, but consistently. The effect of sampling frequency on these two groups of measures are explored and simulations are performed to estimate how much data are required to overcome the uncertainty of a limited sampling frequency. Both simulated and real data are used to estimate the temporal uncertainty of data produced by low sampling frequencies. The aim is to provide easy-to-use heuristics for researchers using eye-tracking. For example, we show how to compensate the uncertainty of a low sampling frequency with more data and postexperiment adjustments of measures. These findings have implications primarily for researchers using naturalistic setups where sampling frequencies typically are low.

Although we experience the visual world as a continuous, richly detailed space we often fail to notice large and significant changes. Such change blindness has been demonstrated for local object changes and changes to the visual form of whole images, however it is assumed that total changes from one image to another would be easily detected. Film editing presents such total changes several times a minute yet we rarely seem to be aware of them, a phenomenon we refer to here as edit blindness. This phenomenon has never been empirically demonstrated even though film editors believe they have at their disposal techniques that induce edit blindness, the Continuity Editing Rules. In the present study we tested the relationship between Continuity Editing Rules and edit blindness by instructing participants to detect edits while watching excerpts from feature films. Eye movements were recorded during the task. The results indicate that edits constructed according to the Continuity Editing Rules result in greater edit blindness than edits not adhering to the rules. A quarter of edits joining two viewpoints of the same scene were undetected and this increased to a third when the edit coincided with a sudden onset of motion. Some cuts may be missed due to suppression of the cut transients by coinciding with eyeblinks or saccadic eye movements but the majority seem to be due to inattentional blindness as viewers attend to the depicted narrative. In conclusion, this study presents the first empirical evidence of edit blindness and its relationship to natural attentional behaviour during dynamic scene viewing.

Eye tracking is increasingly being used in Educational Science and so has the interest of the eye tracking community grown in this topic. In this paper we briefly introduce the discipline of Educational Science and why it might be interesting to couple it with eye tracking research. We then introduce three major research areas in Educational Science that have already successfully used eye tracking: First, eye tracking has been used to improve the instructional design of computer-based learning and testing environments, often using hyper- or multimedia. Second, eye tracking has shed light on expertise and its development in visual domains, such as chess or medicine. Third, eye tracking has recently been also used to promote visual expertise by means of eye movement modeling examples. We outline the main educational theories for these research areas and indicate where further eye tracking research is needed to expand them.

The visual behaviour of consumers buying (or searching for) products in a supermarket was measured and used to analyse the stages of their decision process. Traditionally metrics used to trace decision-making processes are difficult to use in natural environments that often contain many options and unstructured information. Unlike previous attempts in this direction (i.e. Russo & Leclerc, 1994), our methodology reveals differences between a decision-making task and a search task. In particular the second (evaluation) stage of a decision task contains more re-dwells than the second stage of a comparable search task. This study addresses the growing concern of taking eye movement research from the laboratory into the ‘real-world’, so findings can be better generalised to natural situations.

Learning is a complex phenomenon and education researchers are increasingly focussing on processes that go into it. Eye tracking has become an important tool in such research. In this paper, we focus on one of the most commonly used metrics in eye tracking, namely, fixation duration. Fixation duration has been used to study cognition and attention. However, fixation duration distributions are characteristically non-normal and heavily skewed to the right. Therefore, the use of a single average value, such as the mean fixation duration, to predict cognition and/or attention could be problematic. This is especially true in studies of complex constructs, such as learning, which are governed by both cognitive and affective processes. We collected eye tracking data from 51 students watching a 12 min long educational video with and without subtitles. The learning gain after watching the video was calculated with pre- and post-test scores. Several multiple linear regression models revealed a) fixation duration can explain a substantial fraction of variation in the pre-post data, which indicates its usefulness in the study of learning processes; b) the arithmetic mean of fixation durations, which is the most commonly reported eye tracking metric, may not be the optimal choice; and c) a phenomenological model of fixation durations where the number of fixations over different temporal ranges are used as inputs seemed to perform the best. The results and their implications for learning process research are discussed.

We investigated whether levels of reading ability attained through formal literacy are related to anticipatory language-mediated eye movements. Indian low and high literates listened to simple spoken sentences containing a target word (e.g., "door") while at the same time looking at a visual display of four objects (a target, i.e. the door, and three distractors). The spoken sentences were constructed in such a way that participants could use semantic, associative, and syntactic information from adjectives and particles (preceding the critical noun) to anticipate the visual target objects. High literates started to shift their eye gaze to the target objects well before target word onset. In the low literacy group this shift of eye gaze occurred only when the target noun (i.e. "door") was heard, more than a second later. Our findings suggest that formal literacy may be important for the fine-tuning of language-mediated anticipatory mechanisms, abilities which proficient language users can then exploit for other cognitive activities such as spoken language-mediated eye gaze. In the conclusion, we discuss three potential mechanisms of how reading acquisition and practice may contribute to the differences in predictive spoken language processing between low and high literates.

Short-form video platforms are major channels for conflict news, yet how viewers in different national contexts process such content and evaluate its sources remains unclear. This study combined eye tracking with pre- and post-exposure surveys among 124 university students (62 Korean and 62 Chinese) who viewed two native TikTok news posts about the Russia–Ukraine war, one from Korea’s MBN and one from China’s People’s Daily. Gaze was recorded at 60 Hz using a Tobii Pro Nano, with dynamic areas of interest defined for military imagery, people, and subtitles. Source-directed HMP, based on perceived ideological distance and source credibility, was assessed before and after exposure. Korean participants fixated longer on military imagery in both clips (d = 1.27 and 1.11), whereas Chinese participants attended longer to people in the Korean clip (d = −0.48). Subtitle-attention differences showed opposite directions across the two clips, with each group looking longer at subtitles in the clip produced in the other country. Baseline source-directed HMP was higher for the Korean outlet in both groups and was highest among Chinese participants. Across the fixed-order viewing session, HMP increased among Korean participants toward both outlets, whereas Chinese participants showed little change. Separately, among Korean participants, longer attention to people in the Chinese clip was associated with lower post-session HMP toward that outlet. These findings document cross-national differences in visual attention and associations between attention and source evaluation within two specific short-form conflict-news videos.

Transferring gaze estimation models from mobile terminals to in-vehicle driving scenarios faces challenges from differences in device form, viewpoint, and imaging conditions. To address this, this study proposes a cross-scene adaptation framework that integrates composite multi-stage transfer learning with distributed multi-camera fusion for personalized in-vehicle gaze estimation. The framework builds upon a multi-level information element fusion baseline (MIEF) and explores three transfer paths (CMP1–CMP3) for progressive personalized adaptation from a large-scale mobile source domain to an in-vehicle target scenario. A distributed multi-camera platform is established, producing gaze calibration data (GCD) for cross-session training and driving gaze and road scene data (DRD) for visualization validation. A Multi-Camera Fusion Model (MCF) is designed with two paradigms, MCF-Lite and MCF-Plus, to balance accuracy improvement and computational complexity. Experimental results demonstrate that the composite multi-stage transfer learning path CMP3 achieves an average error of 0.277 across camera views, with a best single-camera mean error of 0.244. Building on this, the distributed MCF-Plus model with the full C1 + C2 + C3 configuration further reduces the mean error to 0.160 and the standard deviation to 0.127, with 96.88% of predicted gaze points falling within the target calibration block (Error < 0.5). The proposed method provides a feasible technical pathway for personalized adaptation of gaze estimation models from mobile-terminal source domains to in-vehicle multi-camera target scenarios, and offers preliminary experimental evidence for gaze behavior perception and driving gaze heatmap generation in real environments.

This study examined whether university students display myside bias during and after reading conflicting socio-scientific issue (SSI) texts about genetically modified foods. Fifty-seven students read supporting and opposing claims while wearing eye-tracking glasses. Visual myside bias, defined as greater visual attention to information consistent with readers’ pre-reading stance than to information inconsistent with that stance, was assessed using percent time spent (PTS) and revisited fixation count (RFC) in myside and otherside areas of interest. Prior knowledge, scientific epistemic beliefs, epistemic emotions, and a post-reading argument generation task were also assessed. Students devoted significantly more visual attention to myside information on both PTS and RFC, showing that myside bias emerged during reading as well as in post-reading argument generation. Prior knowledge and scientific epistemic beliefs negatively predicted both visual and post-reading bias. Negative epistemic emotions were positively correlated with both bias measures but were not significant after cognitive variables were controlled. Longer viewing time and more frequent revisits did not necessarily indicate higher-quality informal reasoning; when directed toward myside information, they reflected stance-consistent processing. These findings provide process-based evidence of biased SSI reading and highlight knowledge and epistemic beliefs as potential supports for more balanced, evidence-oriented engagement with conflicting information.

Word decoding as a foundational reading skill is significantly associated with phonological awareness in children with typical development as well as children with intellectual disabilities. Phonological awareness is often assessed using traditional behavioral methods, which may underestimate abilities, particularly in individuals who are difficult to test due to behavioral, communication or attentional difficulties. This study tested whether an eye-tracking “looking-while-listening” paradigm provides an additional recording option which is appropriate and potentially informative to examine the cognitive process while solving phonological awareness tasks in the assessment of children with intellectual disabilities. Fifty-nine children with mild to moderate intellectual disabilities (aged 8–14 years) completed sound, syllable, and phoneme blending and segmentation tasks in paper-based and eye-tracking formats. Participants were classified as proficient or non-proficient based on behavioral performance in the paper-based format. Eye-tracking indices included fixation duration, counts, revisits, and first fixation on target, phonologically similar, and distractor images. Proficient participants showed longer fixation durations and more fixations on target images, as well as greater attention to phonologically similar competitors than distractors, compared to non-proficient participants, who showed no such differentiation. These findings suggest that eye-tracking is a process-oriented method for assessing phonological awareness in children with intellectual disabilities and may capture cognitive mechanisms not reflected in traditional assessment procedures.

Objective: This study employed eye-tracking and ERP to investigate structured pattern processing in basketball players of different skill levels. Methods: A skill-level comparison (skilled vs. less-skilled) was adopted. Participants viewed static point-light displays depicting basketball half-court configurations, with structured (typical tactical formations) and unstructured (random positions) conditions randomly presented. Participants predicted offensive actions while behavioral, eye-tracking, and ERP data were simultaneously recorded. Results: Skilled players showed higher decision accuracy than less-skilled players under structured conditions but not under unstructured conditions, whereas they responded significantly faster under both conditions, with a larger group difference under structured conditions. For pupil diameter, skilled players showed smaller pupil diameters than less-skilled players under both conditions, while within the skilled group pupil diameter was larger under structured than unstructured conditions. Eye-tracking revealed fewer total fixations and a distinct gaze distribution in skilled players—more fixations on opponents and the ball, fewer on open space—along with larger pupil diameters under structured conditions, suggesting enhanced cognitive engagement. ERP data showed that skilled players exhibited larger P300 and LNC amplitudes under structured conditions, reflecting enhanced semantic mapping and schema-based retrieval. Conclusions: These findings are consistent with a theoretical perspective in which expertise may involve a shift from “pattern recognition” toward “abstract representation,” rather than a reduction in neural activity. However, abstract representation, neural information density, and semantic encoding were not directly measured in the present study. The Transformer architecture is therefore offered as a conceptual analogy—its multi-head self-attention corresponds to skilled players’ hierarchical visual sampling, its encoder to semantic mapping (P300 enhancement), and its memory integration to schema-based retrieval (LNC enhancement). These findings provide a basis for structured situational training in sport decision-making.

Conventional eye trackers are difficult to deploy in fashion-runway settings because they require head stabilization, wearable devices, close-range cameras, or infrared illumination. This study develops a far-field, non-contact eye-tracking framework and prototype system for measuring target-directed visual attention in runway-viewing settings using standard cameras. The framework integrates eye-region normalization, 3D gaze estimation, individualized homography-based point-of-regard mapping onto a scene plane, adaptive filtering, DBSCAN-based outlier removal, and kernel density estimation. In Experiment 1, 16 participants completed a controlled calibration-grid benchmark with the proposed system and EyeLink 1000 Plus. Compared with the EyeLink 1000 Plus, the proposed system exhibited higher positional error (Apos: 2.50±0.25° vs. 1.74±0.55°) and a higher value on the processed-output spatial-precision measure (Aspa: 2.31±0.24° vs. 1.02±0.37°). These results characterize end-to-end localization under the calibrated benchmark geometry and provide a controlled reference for the subsequent AOI-level evaluation. In Experiment 2, an independent sample of 16 participants completed an instructed right chest targeting task at 2 m, 4 m and 6 m. AOI-retained sample percentages were 80.4%, 97.3%, and 96.0%, respectively, and gaze-density maps concentrated within the predefined upper-body target region. These findings support the feasibility of target-directed AOI-level localization at far-field distances without chin-rest stabilization under the tested simulated runway-observation protocol.

AOI margin and object height affect gaze assignment; this methodological case study separates them. In a block-imitation task by ten participants, we compared, on the same 4798 fixations, the printed working area (object and support), that area plus a 19 mm margin (separately measured gaze error), and that region raised to object height; the last two differ only in height. Height alone raised the copy area’s dwell share in all ten participants (median +2.4 percentage points), as geometry dictates. For the model’s area, whose region starts on the turntable and can lose gaze, the median was +0.4 points (−5.7 to +32.0), with five rising and five falling. In this layout, the margin moved medians more (copy +7.1, unassigned −14.5). Raised, model and right-tray regions overlapped at every viewpoint; widening them to 40 mm added a median of 0.81 points of assigned time but raised the share qualifying for multiple regions from 0.0% to 13.1%. Two raters judged 200 fixations: the raised region matched their labels more often but also assigned an area where they saw only mat; more assignment is not evidence of accuracy. Size and height are separable choices to report per participant, and their weight depends on layout, tracker and margin.

Background: Many neurological and cognitive disorders have early oculomotor hallmarks. The Oculo-Cognitive Addition Test (OCAT) is a quick, objective screening tool that measures eye movement and time-based biomarkers of cognitive processing during simple mental addition tasks in under two minutes. Normative values for age, sex, education level, and genetic predisposition to Alzheimer’s disease must be established so cognitively normal populations are not misdiagnosed. Methods: 382 patients completed OCAT, and raw gaze data were processed to derive fixations, saccades, blinks, pupillary dynamics, and time-based features. Separate multiple linear regression models were fitted for each feature with age, sex, education, and apolipoprotein E Type 4 (APOE ε4) carrier status as predictors to establish demographic-adjusted normative equations. Results: Processing time, fixation time, fixation size and fixation area and their variability increased progressively from the first to the third number within each addition sequence, consistent with increasing cognitive workload. Demographic-adjusted multiple linear regression models generated normative equations for individual OCAT feature based on age, sex, education, and APOE ε4 carrier status. These models were used to derive individualized expected values, 95% reference intervals, and z-scores. Conclusions: These demographic-adjusted normative equations enable individualized interpretation of OCAT performance and are necessary steps towards clinical implementation.

Eye tracking offers a non-invasive way of examining social visual attention in children and may support the objective identification of autism spectrum disorder (ASD). However, small-sample studies are often affected by individual differences, inconsistent feature selection, and limited integration of different gaze representations. This study explored a dynamic and static multiscale feature fusion framework for classifying children with pre-existing clinical ASD diagnoses and typically developing (TD) children using eye-tracking data collected during an emotion recognition task. After quality screening, 44 children aged 4–7 years were included (18 ASD and 26 TD). Static statistical features, dynamic sequences, early feature concatenation, and multiscale fusion were evaluated using participant-independent data partitioning, with static feature selection restricted to the training participants in each split. CNN–LSTM with multiscale fusion achieved an accuracy of 0.78 ± 0.08, ASD recall of 0.65 ± 0.22, F1-score of 0.71 ± 0.12, and AUC of 0.76 ± 0.16. A fully nested leave-one-participant-out evaluation provided additional internal validation of participant-level classification. Overall, the results indicate that different approaches to combining static and dynamic gaze representations may lead to different classification outcomes, while further validation in larger independent samples is needed.

Assessing semantic representations learned by language models remains challenging because conventional intrinsic benchmarks capture limited aspects of meaning and often correlate weakly with downstream performance. Eye tracking offers complementary, cognitively grounded evidence: gaze measures recorded during reading and scene viewing index online processing and attentional selection, although they should not be treated as readouts of semantic representations. This narrative review and methodological framework synthesizes research linking distributional and contextual language representations to eye-movement behavior, focusing on semantic relatedness, predictability, surprisal, model scale, layer-dependent alignment, and model–human correspondence. Evidence from naturalistic reading corpora shows that embedding-derived relatedness and language-model surprisal explain variance in fixation measures, while recent work demonstrates that cognitive alignment depends on model size, layer, tokenization, task, and measurement regime. We propose extending this approach from population-level model evaluation to observer-specific gaze-derived relational structure. For visual scenes, gaze transitions can be represented as candidate choices and relational graphs and compared with multiple semantic-relation matrices derived from language or vision–language models. Because gaze transitions are influenced by spatial distance, object size, salience, task demands, context, and preprocessing decisions, these factors must be controlled and, where causal isolation is intended, manipulated independently of semantic relations. We propose combining candidate-normalized hierarchical choice models, residualized gaze relations, representational similarity analysis with reliability and uncertainty assessment, and required independent behavioral validation to characterize convergence and divergence between model semantic geometry and observer-specific relational organization.