## 1 Introduction
### Background and Motivation
#### 1.1.2 Current State of Eye-Tracking Technology in Educational Environments  
Several studies indicate that applying eye-tracking techniques can significantly enhance the educational experience outside the laboratory [6; 8; 13]. However, research also indicates differences in gaze behavior between static trackers used in laboratories and portable alternatives tested in real-world settings [24; 25]. Considering naturalistic applications, [PERSON] et al. (2018) examined schoolchildren's learning and visual interactions within a science museum by employing a mobile eye tracker [26]. This device comprised eyeglasses with integrated cameras, enabling the capture of the environmental context and gaze behavior. The findings from this study illustrate that mobile eye tracking can effectively measure learners' attention and engagement, ultimately improving the design of educational resources. Another study employed a mobile eye tracker to investigate the attentional focus of children aged 6 to 8 years during a robotic education activity over a six-month period [27]. The eye-tracking results showed that children exhibited increased engagement with the robotic education activities and showed enhanced information processing speed. This research underscores the role of eye-tracking data in evaluating the efficacy of interactive learning environments. Regarding eye tracking teaching applications, training methods employing experts' fixation points to guide the gaze patterns (scanpaths) of novice participants have demonstrated their effectiveness over traditional training approaches [28; 29; 30]. For example, [PERSON] et al. (2014) compared traditional technical training to quiet eye training for surgical residents learning one-handed square knot tying. Both groups improved, but the quiet eye training group maintained performance despite heightened anxiety. This group also showed more efficient gaze and hand movements after training than the traditional group [29]. Another study demonstrated that proficient medical students could identify areas of interest (AOI) for diagnostic imaging more rapidly than their novice counterparts [31]. The same study also showed that training novice students resulted in a shift in gaze patterns and increased fixations on AOIs relevant to diagnosis [31]. These findings, coupled with similar studies [32; 33; 34; 35], indicate that the pattern of image viewing differs as students acquire the ability to identify areas of interest crucial for result interpretation. Accordingly, some studies advocate for the use of eye-tracking data to showcase the gaze replay of experienced students to aid novice students in learning to comprehend and interpret texts and images [5; 6; 36; 37]. Considering the possibility of applying eye tracking in education, our research group conducted a primary school study to gather teachers' opinions on the relevance of using eye movement data from students who were solving mathematical problems [38]. The results showed that the teachers found eye tracking relevant for research and understanding student cognition and as an educational tool that could be used in the classroom. According to the teachers' reports, the students' eye movement data can help identify difficulties that students may have trouble expressing [38]. This application appears beneficial in one-on-one interactions between teachers and students, as it can enhance teaching by providing information that allows immediate feedback [39; 40]. While the potential relevance of eye tracking in the domain of education is evident, it is imperative to conduct a comprehensive exploration of the intricacies of this tool to discern its merits and demerits as an educational instrument. Furthermore, gaining a more profound understanding of the disciplines that could benefit from this application's utilization is necessary.