Eye-tracking technology in science education: A systematic review
Eye-tracking technology is increasingly used in science
education research, but its benefits and potential insights remain
debated. This review explores its value and limitations through an
analysis of its applications in the field. We reviewed 103 eye-
tracking studies published between 2014 and 2025 to examine
research areas and topics, instrument usage, participant
demographics, interpretations of eye-movement indicators, and
data processing methods. Results indicate that: (1) Eye-tracking
has consistently attracted attention in science education over the
past decade, with findings published in cognitive psychology,
science education, and educational technology journals;(2) The
three most studied topics are Classroom Contexts and Learner
Characteristics, Students’ Conceptions and Conceptual Change,
and Teaching;(3) Participants were predominantly higher
education students, with most studies involving fewer than 120
participants, and the largest subset involving 30-50 participants;(4)
Tobii, SR Research, and SMI are the most frequently used eye-
tracker brands;(5) The division of AOIs mainly depends on
research objectives and experimental tasks, with most based on
functional attributes;(6) Eye-movement indicators fall into three
categories: cognitive processing, attention distribution, and search
strategies. Fixation count, total fixation time, and fixation duration
are the most commonly used; (7) All studies used descriptive
statistics, with some also incorporating emerging methods like
complex network and entropy analysis.
Formation and Development of Mental Models in Partial and Conditional Driving Automation
With the introduction of assisted and automated driving functions, driver-vehicle interaction fundamentally changes. In that context, drivers’ mental models of these functions play a central role. However, due to the novelty of these systems it can be assumed that a lack of knowledge and misconceptions of automated functions are common among drivers. For this reason, this thesis sought to shed light on the question of how the formation of adequate mental models can be supported, and to derive recommendations on the design of driver instruction for assisted and automated driving functions. In a first study (N = 45), the effect of lack of information prior to the first assisted/automated drive on drivers’ mental model formation, attitudes, and interaction with the automated vehicle was assessed. The results of this study emphasize the relevance of driver instruction and its benefits for mental model formation and attitudes towards the vehicle. Based on these findings, the focus of the following three studies was to develop recommendations for approaches to driver instruction. In that context, intrinsic motivation to learn can be expected to be central to enhance learning outcomes. In an online study (N = 220), elements aimed at enhancing learning motivation were added to an instruction on assisted and automated functions, and their effects on learner motivation and mental model formation was assessed. Results indicate that elements providing feedback to the learner on their progress on the instruction help to increase learning motivation. Based on this finding, a gamified instruction was developed and subsequently evaluated in a driving simulator study (N = 65). Gamification is expected to increase intrinsic motivation and thus learning outcomes. Indeed, this study showed that gamification benefits learning motivation, mental model formation, and reliance behaviour. In order to make user education easily accessible to drivers, the fourth study within this thesis comprised the development and evaluation of a tutorial concept that supports drivers during their first drive with an automated vehicle. Results (N = 32) indicate that learning during the drive can be as efficient as before the drive, and benefits acceptance of the automated driving function as well as driver interaction with it. Overall, this thesis provides recommendations for the design of driver education for drivers of current and future automated vehicles. It emphasizes the need to consider learner motivation as a central element of instructional design and provides evidence of the positive effects that low threshold driver education for automated functions can have.
How does campus-scape influence university students’ restorative experiences: Evidences from simultaneously collected physiological and psychological data
"Time in nature" is widely acknowledged as beneficial for physical and psychological health. The landscape environment of campus – referred to as "campus-scape" – plays a crucial role in influencing students’ mental health. It provides outdoor spaces where university students sought for relief and recreation, yet it remains under-researched. In this study, we address a limitation in the static assessment of restorative effects of campus-scape, and extend the focus from visual to non-visual and event landscape, using simultaneously collected psychological and physiological data from an on-site walking experiment (n = 40). This study examined how different types of campus-scape affect university students' restorative experiences by analyzing stress and attention restoration using wearable sensors, alongside perceptional psychological data from questionnaires and interviews. Our results revealed significant differences in the restorative effects of various campus-scape, and the influences were further characterized by visual, non-visual, and event landscape. We have several key findings: (1) 93 % of students reported above-medium stress levels and 72 % experience attention fatigue, highlighting a strong need for restorative campus-scape; (2) Patchy green-blue landscape performs best in stress recovery, followed by linear green-blue landscape and teaching spaces, while living spaces especially the commuting paths were the least restorative, as indicated by physiological electrodermal activity (EDA) and psychological perceived restorative scale (PRS).Meanwhile, most participants experienced attention restoration post-walk across campus-scape types, interestingly subjective self-reported data (FS-14) underestimated the effects compared with objective tests (DSB and TMTB); (3) Within visual landscape, lower landscape segmentation, fewer building views, more welldesigned landscape facilities, and abundant waterbodies, green, and sky views are significantly associated with better stress recovery; (4) Non-visual landscape like thermal conditions, soundscape, and olfactory landscape, along with event landscape–occasional, staged, and routine events–also influence the restorative effects of campus-scape. The aesthetic qualities of campus-scape and capacity for recreational activities are key to students' restorative experiences. Therefore, campusscape designers should prioritize the planning of patchy green-blue spaces and consider enhancing visual, non-visual, and event landscape simultaneously in design guidelines to improve university students' mental well-being.
Image-analysis-based method for exploring factors influencing the visual saliency of signage in metro stations
Many studies have been conducted on the effects of colour, light, and signage location on the visual saliency of underground signage. However, few studies have investigated the influence of indoor visual environments on the saliency of pedestrian signage. To explore the factors that influence the visual saliency of signage in metro stations, we developed a novel analysis method using a combination of saliency and focus maps. Then, questionnaires were utilised to unify the various formats of results from the saliency and focus maps. The factors that influence the visual saliency of signage were explored using the proposed method at selected sites and validated through virtual reality experiments. Additionally, this study proposes an image-analysis-based method that reveals the multilevel factors affecting pedestrian attention to signage in underground metro stations, including spatial interfaces, crowd flow, and ambient light. The results indicate that crowd flow has the greatest impact on pedestrian attention to signage. The findings of this study are expected to improve the wayfinding efficiency of pedestrians and assist designers in producing high-quality metro experiences.
Impact of multi-dimensional cognitive demands on takeover performance, physiological and eye-tracking measures in conditionally automated vehicles
Before fully autonomous vehicles come true, drivers are still required to be responsible for driving safety and take over control of the vehicle when prompted by takeover requests in conditionally automated vehicles. Thus, drivers’ takeover performance can affect the safety of conditionally automated driving. However, though cognitive distraction can impair takeover performance in general, the influence of multi-dimensionality in the cognitive resources was under-investigated. At the same time, it is unknown how physiological and eye-tracking metrics are associated with different modalities of cognitive tasks in conditionally automated vehicles. Thus, through a driving simulation study with 42 participants, we investigated the effects of multidimensional cognitive demands, as imposed by multiple types of non-driving-related tasks, on drivers’ takeover performance, physiological responses, and eye-tracking metrics in conditionally automated vehicles. Results showed that certain takeover performance (i.e., vehicle speed and lateral acceleration), and physiological and eye-tracking metrics (i.e., differences between consecutive R-peaks, skin conductance level, variation in respiratory intervals, number of fixations, number of saccades and saccade angle) are still responsive to cognitive load in the context of driving automation. Further, the modality of the cognitive tasks can moderate the takeover performance (i.e., takeover time) and certain physiological (i.e., ratio of spectral power in the low- and high-frequency range and respiration depth) metrics. These findings suggest that, in future conditionally automated vehicles, in-vehicle task designs should consider the modality of the cognitive demands for driving safety and for the performance of the driver monitoring systems.
In-Vehicle Displays for Supporting Operation of Driving Automation Systems: Design and Evaluation using Driver Gaze Measures
In-vehicle displays can support the safe operation of driving automation systems, but a challenge lies in balancing the information conveyed against situational demands. Driver gaze measures are a useful tool for evaluating such displays as they can provide a proxy for driver attention, particularly when the driver is not physically controlling the vehicle. The objective of this dissertation is to systematically identify the design space for displays aimed at supporting safe operation of automation and provide a comprehensive review of their evaluation using gaze measures. First, a scoping literature review revealed extensive research focus on takeover requests, with relatively less focus on informational displays that communicate the automation’s intent or explicitly identify hazards. Surprisingly, there was little focus on displays that monitor and manage driver attention, which are becoming increasingly available and mandated in some jurisdictions. The gaze measures adopted for evaluation mostly relied on static areas of interest that were not dependent on traffic context.
Inflating system expectations prior to SAE level 3 automated vehicle use: effects on monitoring behavior, resumption of control, and attitudes toward driving …
Increasing levels of vehicle automation bring new risks to drivers, particularly those who are using a new automated driving system (ADS). The overreliance on partially automated advanced driver assistance systems (SAE L2 ADAS) has led to crashes, a concern that might escalate with conditional ADS (SAE L3), which require timely driver intervention. This study examines the impact of how L3 ADS’ capabilities and limitations are communicated to users on their subjective attitudes toward ADS and their driving behavior and performance, particularly concerning safety.
Method
In a driving simulator study, participants received introductory videos about the role of drivers at different automation levels, the capabilities and limitations of L3 ADS, and its human–machine interface (HMI). Videos concluded with either “Highlighted Benefits” of higher automation levels, reflecting current marketing trends of ADAS and ADS, or an “Explicit Reminder” of driver responsibilities in L3 ADS usage. Participants then completed three driving simulator runs (repeated measures) during or after which visual monitoring behavior, take-over performance, and subjective attitudes (trust and acceptance) toward the ADS were gathered.
Results
Participants resumed control when receiving uncertainty alert from the ADS across both introductory information conditions, with minor differences in take-over performance and monitoring behavior. No significant differences were observed in road monitoring behavior, take-over performance, and subjective attitudes between conditions, except for subjective familiarity ratings, which decreased over runs for the Explicit Reminder group compared to the Highlighted Benefits group. Both conditions showed take-over performance improvements, particularly after practice.
Conclusions
Successful crash avoidance in both groups indicates that graded warnings and practice can effectively improve take-over performance. This similarity in outcomes suggests that introductory information about ADS may not significantly affect monitoring behavior and performance of ADS users. These results highlight the potential for such systems to mitigate ADS complacency and promote safer resumption of vehicle control during automation failures.
Informing Drivers of ADAS Capability: Effects of Functionality vs. Limitation-Focused Training on Takeover in Silent Failure Scenarios
As advanced driver assistance systems evolved to incorporate more complex features, enhancing drivers’ understanding of the ADAS capability becomes crucial for ensuring safe and effective human-automation collaboration in critical system failure situations. However, although academia has emphasized the importance of informing drivers about the limitations of ADAS, most ADAS information conveyed in the sales channel remains basic or is mainly positive, highlighting the functions rather than the limitations of the ADAS. Thus, it is essential to comprehend how such positive information influences users’ perception of ADAS and whether additional limitation information enhances or hinders drivers’ understanding of ADAS. Further, most previous studies validated the effects of training in system failures with takeover requests (TORs), which are different from real-world scenarios, where silent failures without TORs dominate. Thus, this study investigates the effectiveness of various training strategies in conveying ADAS capabilities (including functionality-focused, limitation-focused, and combined training) to drivers. In a driving simulator experiment with 32 participants, we evaluated how drivers behave in silent failure scenarios after receiving different training programs. The results show that functionality-focused training induces hesitation in critical scenarios, while limitation-focused training encourages vigilance but triggers over-reactions during takeover events. In contrast, combined training significantly enhances situational awareness and takeover performance without increasing mental workload, underscoring the importance of a balanced educational approach. These findings highlight the role of driver training, even in silent failures, emphasizing the need for comprehensive training that integrates both system functionalities and limitations and provide insights for optimizing human-automation collaboration in safety-critical scenarios.
Investigating effects of temperature and CO2 on driver drowsiness in the context of conditional automated driving
With the introduction of conditional automated driving, drivers are freed from continuous control but must remain alert for takeover requests. This study examines how in-cabin temperature (22.5 °C, 25 °C and 27.5 °C) and CO2 (4200 and 1200 ppm) influence driver drowsiness and physiological responses under conditional automated driving. A driving simulator experiment involving 60 participants was conducted, collecting subjective ratings, eye-tracking and physiological data. Results showed that cooler temperatures were associated with lower drowsiness levels compared to neutral temperatures. However, physiological responses may mainly reflect thermoregulation when temperature varies, obscuring drowsiness-related changes. Further, although CO2 concentration did not significantly affect subjective drowsiness, higher CO2 levels attenuated cardiovascular and autonomic activity, suggesting CO2 effects on physiological responses can emerge before conscious awareness. These findings suggest that climate control systems in automated vehicles should balance comfort, efficiency and driver alertness, while physiology-based driver monitoring systems should incorporate environmental data to detect drowsiness earlier.
Modulating driver visual behavior in highway tunnel groups through rhythm-based visual cues
Drivers navigating highway tunnel groups face complex and repetitive lighting environments, which increase cognitive load and compromise safety. This study aimed to evaluate the effectiveness of rhythm-based visual cues in improving perceptual orientation and regulating driver visual behavior in tunnel group scenarios.
Methods
To determine the most suitable rhythm pattern for visual guidance, a rhythm adaptability selection process was first conducted using a fuzzy evaluation method. A simulated driving experiment was then performed in UC-win/Road, exposing participants to varying lighting conditions with and without rhythm-based visual cues. Driver eye-movement metrics, including fixation duration, saccade amplitude, and saccade velocity, were used as behavioral indicators to assess visual load and attention regulation.
Results
Extended tunnel driving was associated with increased fixation durations, a dominance of small-angle saccades (0°–10°), and slower saccade velocities—patterns indicative of visual fatigue and decreased attentional control. The introduction of rhythm-based visual cues significantly improved visual behavior by reducing fixation durations, lowering the frequency of small-angle saccades, and enhancing saccade dynamics. These improvements were more prominent under low-light conditions, indicating better visual adaptability and engagement.
Conclusions
Rhythm-based visual cues provide an effective and energy-efficient alternative to increased tunnel illumination by directly targeting visual behavior. The findings support the application of perceptually informed environmental design strategies that utilize rhythm sensitivity to improve driver safety in highway tunnel groups.
