Jul 2026· Trends in Psychology· 0 citations· 86 references
Abstract
The ability to comprehend and interpret visualizations has garnered increasing attention in recent years. Individuals with specialized knowledge and experience in a particular field exhibit distinct patterns in how they perceive, process, and retain information related to that area. Extensive research across various domains has demonstrated that expertise confers perceptual and cognitive benefits in engaging with domain-relevant information. Eye-tracking methodology has provided significant insight into some of the perceptual mechanisms underlying performance differences between experts and novices in various professional settings, including aviation, car driving, medicine, arts, cartographic research and sports. The opportunity to access tacit expert knowledge, to improve efficiency of task performance and potentially to enhance safety measures has gained growing attention over the past years. This article conducts a systematic literature review to consolidate literature describing the application of gaze behavior as an adjunct tool to traditional teaching methods. Building on the proposed conceptual framework, we systematically reviewed the training potential of eye movements. Our results reveal that gaze-trained individuals exhibit a performance advantage over traditionally trained counterparts and that the impact and feasibility of expert skills transfer through gaze behaviors are moderated by different factors. We summarize the benefits of using expert gaze as a visual cue (e.g. EMMEs) in terms of attention-modeling processes, human performance and safety in work environment.
To overcome the limitations of conventional design assessment in capturing instant cognition and visual dynamics, this paper proposes a multimodal evaluation method for visual design effectiveness based on eye-tracking technology. By integrating dynamic region-of-interest sequence analysis with retrospective cognitive attribution, the method captures both the spatial flow and temporal dynamics of visual attention. A contextual task is designed to simulate realistic viewing behavior while maintaining experimental control, guiding participants through goal-oriented browsing under standardized presentation conditions. Dynamic region-of-interest sequence analysis is then used to measure gaze retracing rate and evaluate the clarity of information hierarchy. Retrospective interviews and visual entropy analysis are combined to link objective eye-movement trajectories with subjective semantic interpretation. Experimental results show that the method effectively differentiates design effectiveness under different contrast ratios. The high-contrast group has the shortest initial fixation time (180 ± 38 ms) and the lowest gaze retracing rate (26.1 ± 5.9%). Gaze retracing rate is negatively correlated with semantic comprehension accuracy (r = -0.81), supporting continuous evaluation from perception to cognition.
Xinzhen Zhuo, Zhixiong Hu, Yang Lin· Advanced Electromagnetics· 0 citations
This study examined the role of predictive processing mechanisms in naturalistic visuomotor skill learning. We investigated whether the acquisition of an interceptive skill was characterised by encoding and using learned probabilistic associations. Forty-five participants were randomly assigned to either an intervention or control group and practiced intercepting bouncing balls in virtual reality across two sessions. Only the intervention group received probabilistic visual cues - specifically, ball and room colours - that signalled likely bounce trajectories, offering an opportunity to learn and exploit these associations. We assessed task performance (interception rate, return accuracy), anticipatory gaze behaviour (predictive fixations and gaze tracking), and pupillary responses to unexpected outcomes. Participants in the training group demonstrated more predictive gaze strategies and physiological surprisal responses to probabilistically unlikely bounce outcomes post training. These findings suggest that encoding probabilistic environmental cues can contribute to effective visuomotor control. The results offer novel evidence for the role of top-down prediction and contextual modulation in visuomotor skills, with implications for training and expertise development in sport. More broadly, this work contributes to an alternate account of expertise as the capacity to encode and exploit environmental regularities through predictive mechanisms.
D. Harris, M. Wilson, S. Vine et al.· Human Movement Science· 0 citations
This study examines how prior knowledge and formal instruction shape visual attention during crime scene investigation (CSI). Using a quasi-experimental pretest-posttest design, we compared a prior-knowledge cadet group (n = 21), a novice cadet group (n = 30), and an expert reference group of active forensic investigators (n = 13). Participants viewed authentic crime-scene photographs while gaze data were recorded for key-evidence and distractor areas of interest (AOIs). Eleven eye-tracking metrics and Lag Sequential Analysis (LSA) were used to characterize attention allocation and gaze transitions. Results show that prior knowledge guided evidence-oriented viewing before instruction, that both student groups improved after one semester of CSI training through different visual-learning pathways, and that eye-tracking detected differences not captured by written tests. The findings support differentiated CSI instruction and the use of formative gaze feedback in law-enforcement education.
Rong-Chi Chang, Liang-Yi Chung· Proceedings of The World Con...· 0 citations
Visual perception is a complex cognitive process that allows humans to extract meaningful information from their environment. Phototexts, artistic and literary compositions that integrate photographic and textual elements, offer a multimodal experience that requires readers to navigate between visual and linguistic modes of interpretation. This study investigates, in naïve participants, the influence of spatial layout configuration, emotional content, enjoyment, and attentional focus on the visual exploration of phototexts. Using eye-tracking technology, we examined participants' gaze patterns, focusing on metrics such as first fixation latency and fixation distribution across areas of interest (AOIs). Additionally, we explored the presence of left-gaze bias in text-photo stimuli systematically counterbalanced to mitigate positional effects. Our findings reveal key aspects of oculomotor behavior, as well as explicit preferences and judgments regarding phototext perception. Eye-tracking data indicated a natural reading bias, with shorter fixation latencies for text regardless of position, alongside a left-gaze bias that emerged specifically for photographs. Interestingly, attention patterns evolved dynamically over time, with an initial focus on text shifting toward the photographic component as viewing progressed. By analyzing phototexts as complex multimodal stimuli, this study provides novel insights into their synergistic effects on attention distribution and perceptual engagement.
N. Langiulli, M. Cometa, R. Coglitore et al.· Scientific Reports· 0 citations
This work proposes two complementary eye tracking methodologies focused on understanding information access. The first study examines the earliest stage of search, the formation of an information need, and the formulation of a query. The second study presents participants with a pre-typed query on a Search Engine Results Page (SERP) containing GenAI content positioned above the traditional ten blue links. Across both studies, the planned analysis examines how user interactions differ from patterns reported in prior literature, and outlines future research directions aimed at deepening our understanding of search behavior in the era of GenAI. By linking visual attention to query behavior across traditional and GenAI-enhanced interfaces, this research contributes toward more intuitive and adaptive search systems that better support evolving information-seeking behavior. The design space for search engine interfaces is vast, but interaction techniques and user interfaces for information access with LLMs remain under-researched and poorly understood. Between 2020 and 2024, 750 preprints related to LLMs were published on arXiv in the field of Information Retrieval, with only 22 mentioning "user interface" in their abstracts [3]. This research will contribute to filling this gap by understanding user behavior, preferences, and cognitive effort in human-AI interactions. Specifically, the goal of this research is to explore how users seek information in the era of GenAI via a series of user lab studies. These studies will be conducted to compare traditional search engines with GenAI-based systems. Based on these lab studies, the aim is to develop new methods that better fulfill users' information needs. Key research questions for this research include: •[RQ1:] How do eye fixations on specific words read before a search session impact query formulations?•[RQ2:] How do eye fixations on specific words read before a search session, together with curiosity about a topic, influence query variations? •[RQ3:] How do individuals read information prior to formulating queries?•[RQ4:] How does user interaction with new search engine interfaces differ from the patterns of scanning search engine interfaces described in the literature? •[RQ5:] How to evaluate search behaviors in the context of information seeking?•[RQ6:] What are the fundamental factors Information Retrieval researchers should investigate when conducting user studies in the era of Generative AI? The work I have described in this research is done under a reasoned approach, but may not account for all user variables such as domain expertise, use of different devices [1], other demographics, anomalous state of knowledge, and cognitive biases [2]. Researchers have attempted to overcome the complexity of understanding human search behavior by creating personas and simulating user behavior. However, this raises concerns that simulated users may not accurately reflect real human behaviors, and assessing the validity of simulated users still remains a challenge [1]. Therefore, conducting both types of studies separately and in combination is important, as each approach can provide valuable insights and collectively contribute to the body of knowledge to understand and improve human-GenAI interactions. The challenge we expect to face when conducting this research is frequent updates to search interfaces. How can we standardize our studies to account for these changes? How do we analyze user behavior when interfaces keep evolving? Should we test multiple interface versions, present our findings, and then provide recommendations? An additional aspect is determining how participants interact with different search tools based on different types of tasks. Do they rely on traditional search engines, generative AI systems, or a combination of both?
Sara Allawati· Annual International ACM SIG...· 0 citations
A publicly available, goal-driven, interactive guide called Generalized Eye Tracking Metrics (GEMs), which supports the learning of metrics, relevant terminology, and analysis approaches as it relates to the user’s research questions and experimental setup.
Lauren E. Horde, Shannon P. D. McGarry, Ciara M. Sibley et al.· Proceedings of the Human Fac...· 0 citations
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