Conference Agenda
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27 SES 16 A: Eye-Tracking Research in Didactics
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27. Didactics - Learning and Teaching
Paper Text–Visual Integration in Complex Geography Tasks: Eye-Tracking and Think-Aloud with High-Achieving Students 1: Jan Evangelista Purkyně University in Ústí nad Labem, Czech Republic (Czechia); 2: Masaryk University, Brno, Czechia Presenting Author:The proposal is situated in didactics—specifically, subject didactics of geography—and examines how high-achieving students with advanced geographical knowledge and skills (participants in the national round of the Geography Olympiad and International Geography Olympiad – iGeo – rounds) solve complex learning tasks that require the integration of written information with visual representations (a map and a diagram) while also working with more open-ended response formats. Such tasks call for higher-order cognitive operations, including the interpretation of spatial data, the reading of visual models, and evidence-based reasoning grounded in those representations. The study has clear international relevance because the stimulus material follows the international iGeo format and is provided in English; the findings therefore have the potential to be potentially transferable across educational contexts where learners engage with similar multimodal tasks and assessment formats. Moreover, the interdisciplinary thematic focus of the tasks (global energy) supports transfer beyond geography to neighbouring domains (e.g., geology, environmental education) and, more broadly, to subjects that routinely rely on maps, diagrams, and data visualisations. The conceptual framework draws on the Cognitive Theory of Multimedia Learning (CTML), which emphasises separate yet interacting channels for verbal and visual information, the limited capacity of working memory, and the need for active processing (selecting relevant information, organising it, and integrating across sources) – (Mayer, 2024). In its contemporary formulation, CTML also addresses which design features support effective learning from combined words and visuals and how this support may differ across conditions and task types (Dirkx et al., 2021). One potentially consequential condition is solving tasks in a foreign language (here, English), which may increase cognitive load and reduce task-solving efficiency (Roussel et al., 2017). This highlights the importance of task design that limits cognitive load while maintaining cognitive demand. From the perspective of geography didactics, it also implies that visuals (maps, diagrams) should not function as mere add-ons; they should carry a substantive share of the cognitive work. Doing so requires learners to strategically allocate attention across sources and to connect them into a coherent explanation rather than treating each component in isolation. Methodologically, the study builds on the growing use of eye-tracking to investigate cognitive processes in education (Liu & Cui, 2025). Recent systematic evidence indicates that eye-tracking is frequently applied in research on multimedia learning and complex task solving, most often using time- and frequency-based indicators (e.g., fixation durations and counts) and drawing theoretically on CTML and cognitive load perspectives (Liu & Cui, 2025). For the geography context in particular, fine-grained patterns of attention—especially shifts between text and visual representations (Popelka et al., 2022) and the distribution of attention across defined areas of interest—provide a plausible window into learners’ integration strategies and potential critical issues (Fairbairn et al., 2023). The core aim of the study is to describe and explain how high-achieving solvers allocate attention between task prompts, responses, and supporting representations (map, diagram, explanatory text) when solving a complex geography task, and how these process characteristics relate to solution success and efficiency. Two research questions guide the analysis: RQ1: How are indicators of visual attention (e.g., task completion time, fixation durations/counts within AOIs, switching between AOIs) related to task success (score) and efficiency? RQ2: Which parts of the material function as critical issues, and which text–visual integration strategies (supported by verbal data) are characteristic of more accurate solutions? Methodology, Methods, Research Instruments or Sources Used The study uses a mixed-methods research design and combines quantitative and qualitative approaches. Specifically, it employs quantitative eye-tracking combined with verbal data from a subsequent think-aloud protocol. The sample consists of N = 17 students aged 16–19 who succeeded in the national round of the Geography Olympiad and actively participated in international rounds (iGeo). Through this selection, the authors operationalise an “above-average” level of geographical knowledge and skills within a competition context. The competition has long relied on tasks that target higher-order cognitive operations, work with visuals, and complex thematic content (Svobodová & Trahorsch, 2025). The stimulus material was a printed worksheet thematically focused on global energy. The stimulus material was entirely in English, which increases the study’s international relevance (e.g., the transferability and applicability of findings to other contexts). The worksheet consisted of three consecutive sub-tasks. The material combines (a) an anamorphic map showing the spatial distribution of electricity production from gas and (b) a diagram of fracking technology, complemented by an explanatory text. Tasks based on these visuals target higher-order cognitive operations (application, analysis). The stimulus material also includes a task targeting a lower-order cognitive operation, specifically comprehension. Participants had access to a printed English dictionary. Solution success is assessed against model solutions (factual correctness of responses). Solution success is then related to eye-tracking metrics in order to identify effective task-solving strategies (e.g., examining the relationship between score and task completion time). Visual attention was recorded using mobile eye-tracking (Tobii Pro Glasses 2) during task solving (video-recorded). For analysis, areas of interest (AOIs) were defined for the task answers and for supporting sources (the map, the diagram, the accompanying text). Basic metrics were used, such as task completion time, number of fixations, total fixation duration, and partial fixation durations within AOIs (Fairbairn et al., 2023). The think-aloud protocol conducted after completing the task supports the interpretation of strategies and critical points within the tasks (Stark et al., 2024). Conclusions, Expected Outcomes or Findings Findings from this selective group of iGeo participants (N = 17) show substantial performance variability: overall scores ranged from 0% to 80% (M = 41%). Eye-tracking further indicates that visuals were not the dominant focus of attention. Of total fixation duration, 9% was allocated to the map (anamorphic map) and 9% to the diagram, whereas the accompanying explanatory text accounted for 27%; the remaining attention was directed to the task prompts and written responses. In terms of multimedia learning, this suggests that even in tasks that include visuals, solvers may proceed in a largely text-driven manner, using visuals selectively as a verification resource rather than as the main basis for reasoning. Consistent with this interpretation, process–performance patterns indicate a negative association between engagement with visuals (time spent and AOI visit counts) and achieved score: higher-scoring solvers attended to the visuals less than lower-scoring solvers. This can be read as evidence of efficient selection (rapid extraction of decisive visual information), but it may also signal that some visuals are not tightly aligned with the assessment core of particular items (i.e., they are didactically weakly aligned). Content analysis of the post-task think-aloud protocols complements these findings. Participants repeatedly identified technical English terminology and fact-oriented items as critical difficulties, while the anamorphic map was perceived as relatively manageable. This pattern is compatible with higher-order reasoning alongside limits in recalling specific declarative knowledge. In sum, (1) the process data point to selective rather than extensive use of visuals, and (2) performance appears more related to purposeful integration of sources than to prolonged visual inspection (Popelka et al., 2022; Stark et al., 2024). (3) Didactically, the results support explicitly linking questions to specific visual elements and providing targeted support for technical terminology in internationally oriented tasks (Roussel et al., 2017). References Dirkx, K. J. H., Skuballa, I., Manastirean Zijlstra, C. S., & Jarodzka, H. (2021). Designing computer-based tests: Design guidelines from multimedia learning studied with eye tracking. Instructional Science, 49(5), 589–605. https://doi.org/10.1007/s11251-021-09542-9 Fairbairn, D., & Hepburn, J. (2023). Eye-tracking in map use, map user and map usability research: what are we looking for? International Journal of Cartography, 9(2), 231–254. https://doi.org/10.1080/23729333.2023.2189064 Liu, X., & Cui, Y. (2025). Eye tracking technology for examining cognitive processes in education: A systematic review. Computers & Education, 229, 105263. https://doi.org/10.1016/j.compedu.2025.105263 Mayer, R. E. (2024). The Past, Present, and Future of the Cognitive Theory of Multimedia Learning. Educational Psychology Review, 36, 8. https://doi.org/10.1007/s10648-023-09842-1. Morita, A., & Fukuya, I. (2025). Integrative processing of text and multiple maps in multimedia learning: An eye-tracking study. Frontiers in Psychology, 16, 1487439. https://doi.org/10.3389/fpsyg.2025.1487439 Popelka, S., Burian, J., & Beitlova, M. (2022). Swipe versus multiple view: a comprehensive analysis using eye-tracking to evaluate user interaction with web maps. Cartography and Geographic Information Science, 49(3), 252–270. https://doi.org/10.1080/15230406.2021.2015721 Roussel, S., Joulia , D., Tricot, A., & Sweller , J. (2017). Learning subject content through a foreign language should not ignore human cognitive architecture: A cognitive load theory approach. Learning and Instruction, 52, 69–79. https://doi.org/10.1016/j.learninstruc.2017.04.007 Stark, L., Korbach, A., Brünken, R., & Park, B. (2024). Measuring (meta)cognitive processes in multimedia learning: Matching eye tracking metrics and think‐aloud protocols in case of seductive details. Journal of Computer Assisted Learning, 40(6), 2985–3004. https://doi.org/10.1111/jcal.13051 Svobodová, H., & Trahorsch, P. (2025). Assessment in geography through geography Olympiads: comparison of results of the Czech National and International Geography Olympiads from 2015 to 2022. International Research in Geographical and Environmental Education, 34(2), 139–155. https://doi.org/10.1080/10382046.2024.2352281 27. Didactics - Learning and Teaching
Paper Teacher Professional Vision for Self-Regulated Learning: A Conceptual Model and Findings from a Classroom Eye-Tracking Study 1: Vytautas Magnus University, Lithuania; 2: University of Turku, Finland Presenting Author:Self-regulated learning (SRL) refers to students’ capacity and skill to actively regulate own thinking, emotional responses, and behaviour to complete academic tasks (Zimmerman, 2002). It is recognised as key for academic success and lifelong learning. Teachers can promote SRL in their classroom instruction in various ways (Dignath & Büttner, 2018), and this support has to be adaptive to different student SRL profiles and needs (Corno, 2005). However, there is a lack of research on teacher noticing of student SRL cues while teaching. Moreover, the research lines on teacher SRL support have focused on teacher assessment, knowledge, and teaching methods for SRL separately. Yet, to understand how teachers can support student SRL adaptively, a holistic approach is needed. Therefore, this research adopts the concept of teacher professional vision as a conceptual lens for investigating teacher practice in the classroom. Teacher professional vision relates to how teachers notice and interpret classroom events and interactions relevant for student learning in light of their own professional and contextual knowledge (van Es and Sherin, 2002). According to Scheiner (2021), teacher professional vision encompasses a dynamic interplay between teacher noticing, professional knowledge, and decisions to act. Thus, professional vision reflects a particular focus on student cues in the process of teaching, which allows teachers to adapt instruction in the moment, in congruence with what they notice about student thinking. The aim of this study was to gain understanding of teacher professional vision in the process of observing and supporting students as self-regulated learners directly in the classroom. For this, firstly, a conceptual model of teacher professional vision specifically for supporting student SRL (TPV-SRL) had been proposed, connecting elements of teacher professional vision (Scheiner, 2021) with teachers’ assessment, understanding, and teaching approaches to SRL support. Secondly, a classroom study was conducted to investigate teacher noticing and knowledge-based reasoning while supporting their students in one lesson. The study addressed the research questions: (1) To what extent student SRL characteristics contribute to variation in the amount of teacher visual attention to students in the lesson, as part of teacher noticing? (2) How do teachers reason about students and supporting student SRL in the classroom? Methodology, Methods, Research Instruments or Sources Used This study followed a mixed methods research design, with 10 teachers and their secondary school students (N=158) as participants. Teachers were asked to teach one lesson wearing a mobile eye tracker that recorded teacher first-person perspective and eye movement. After the lesson, teachers watched this recording and provided explanations of own actions in retrospective think-aloud sessions that were audiotaped. The eye tracking recordings were manually coded by the researcher for visual targets related to students using teacher gaze visit as an eye tracking metric. Also, SRL questionnaires were administered. Students self-reported own SRL practices on SRSI-SR scale (Cleary, 2006). Additionally, each student’s SRL behaviours were rated by their teachers on a SRSI-TR scale (Cleary, & Callan, 2014). Teacher visual attention distribution to students in relation to student SRL scores was analysed with complex regression in MPlus (Muthén, & Muthén, 2017). Teacher retrospective think-aloud recordings were transcribed and analysed with hybrid thematic analysis (Xu & Zammit, 2020). Conclusions, Expected Outcomes or Findings The first research question addressed the extent to which student SRL characteristics contributed to the variation in teacher visual attention on students as part of noticing. The quantitative analyses showed that teachers visually focused more on students whom they perceived as tending to ask questions or seek information in the lesson. However, teachers focused less on students whom they perceived as being able to manage own motivation and behaviour. The second research question addressed teachers’ explanations of own attention and support of student learning in the lesson. The qualitative analyses of teacher think-alouds on their own actions in the lesson revealed that teachers noticed both student behavioural and cognitive cues, to a smaller degree metacognitive cues, as well as student characteristics not diagnostic of SRL. In terms of SRL support, teachers emphasised implicit approaches of strategy modelling and prompting student thinking and independent performance. Teachers also considered student learning differences and aimed to adapt support where possible. In terms of referring to professional knowledge, teachers did not use SRL terminology but referred to SRL-relevant points. Overall, following the conceptual model of TPV-SRL, this study showed that in terms of teacher noticing, more salient student characteristics (help-seeking) contribute to teacher visual attention allocation on students. In terms of teacher reasoning, teachers use a larger variety of characteristics (both diagnostic and non-diagnostic of SRL) to reason about student learning. In terms of SRL support, teachers emphasised intended implicit approaches. This shows that teachers do consider student characteristics and processes important for supporting student SRL when teaching a specific lesson; however, teachers’ noticing of student SRL cues and reasoning about student learning is not fully conductive of SRL support. This implies including and studying promotion of student SRL as a teaching competence, especially with a focus on the diagnostic cues of student SRL. References Cleary, T. J. (2006). The development and validation of the Self-Regulation Strategy Inventory—Self-Report. Journal of School Psychology, 44(4), 307–322. https://doi.org/10.1016/j.jsp.2006.05.002 Cleary, T. J., & Callan, G. L. (2014). Student self-regulated learning in an urban high school: Predictive validity and relations between teacher ratings and student self-reports. Journal of Psychoeducational Assessment, 32(4), 295–305. https://doi.org/10.1177/0734282913507653 Corno, L. (2008). On teaching adaptively. Educational Psychologist 43, 161–173. https://doi.org/10.1080/00461520802178466 Dignath, C., & Büttner, G. (2018). Teachers’ direct and indirect promotion of self-regulated learning in primary and secondary school mathematics classes – insights from video-based classroom observations and teacher interviews. Metacognition and Learning, 13(2), 127–157. https://doi.org/10.1007/s11409-018-9181-x Muthén, L. K., & Muthén, B. O. (2017). Mplus user’s guide (8th ed.). Muthén & Muthén Scheiner, T. (2021). Towards a more comprehensive model of teacher noticing. ZDM – Mathematics Education, 53(1), 85–94. https://doi.org/10.1007/s11858-020-01202-5 van Es, E. A., and Sherin, M. G. (2002). Learning to notice: Scaffolding new teachers’ interpretations of classroom interactions. Journal of Information Technology for Teacher Education, 10(4). Xu, W., & Zammit, K. (2020). Applying thematic analysis to education: A hybrid approach to interpreting data in practitioner research. International Journal of Qualitative Methods, 19, 1609406920918810. https://doi.org/10.1177/1609406920918810 Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into practice, 41(2), 64–70. 27. Didactics - Learning and Teaching
Paper 6th Grade Student Strategies Used to Comprehend Environmental Content Information at a Science Centre: Eye-Tracking Study Kaunas University of Technology, Lithuania Presenting Author:Environmental literacy is a part of scientific literacy that allows us to draw informed conclusions about changes caused by human activity, encompassing knowledge, natural phenomena, sustainability goals, environmental contexts, global social problems, and encouraging us to contribute to solving problems (Davidson et al., 2023; Larsen, 2024; Scharon et al., 2024). Scientific literacy is a student's ability to explain phenomena scientifically, interpret data, and make informed decisions in personal, local, and global situations (OECD, 2023). In addition, modern scientific literacy encompasses the ability to recognize misinformation, evaluate the reliability of sources, understand specific scientific texts, and apply this knowledge when making decisions about health, environmental protection, or politics (Valladares, 2021; Osborne & Allchin, 2025). Data from international studies (PISA, 2022) indicate that science literacy scores peaked in 2009 and have declined gradually in OECD countries since then. Two main trends are evident in Europe: a decline in performance among previously leading countries and a widening of the performance gap. Non-formal learning environments that foster interest in science and the critical evaluation of information can help develop students' scientific literacy (Kontkanen et al., 2024). To combine formal education with informal experiences that foster deeper engagement in science among students (Valladares, 2021), teachers can collaborate with science outreach organizations, such as science centres. Previous studies that examined the educational and organizational planning of science centres, student engagement, and behaviour (Lewalter et al., 2025) have shown that exhibition design and interaction with exhibits can help students learn through exploration, develop metacognitive reflection, understand scientific content but also evaluate the reliability of everyday information reasonably (Osborne & Allchin, 2025; Valladares, 2021; Kervinen et al., 2020). Learning at a science centre is self-directed (Zimmerman, 2000), making students the primary participants in their learning process (Martín-García & Dies Álvarez, 2024). Therefore, it is possible to argue that the design of a science centre exhibition serves as a bridge between the exhibit and the learner, not only in terms of aesthetics but also in educational content (Eren-Şişman et al., 2020). Science centres create interactions between the science centre exhibit and the students' thinking, acting as educational intermediaries that connect visitors' internal knowledge with knowledge and meanings that promote awareness, as visitors use their existing experience to give meaning to exhibits, thereby supplementing their experience with new knowledge (O’Connor et al., 2020). From an educational research perspective, investigating how visitors think and learn while interacting with exhibits is complex and may require technological tools. However, videos can capture instances of mediation, and interaction with exhibits can only be inferred. Eye-tracking technology can be used to determine a student's eye movements as a proxy for attention. This technology helps to identify specific features of exhibits that most attract visitors' attention and elicit the greatest cognitive engagement and emotional response from students (Krogh-Jespersen et al., 2020). Students at science centres often miss important information, such as instructions or explanations on display panels, even though they may appear to be observing the entire exhibit (Magnussen et al., 2017; Teo et al., 2024). Therefore, this study focuses on the mediation potential of exhibits, the perception of exhibit content, and cognitive load (Krogh-Jespersen et al., 2020), yet research on these aspects of education remains limited. This problem area raises the following research questions: Q1: How do students perceive the science centre’s environmental literacy exhibits? Q2: What interaction between the science centre’s exhibits and students' environmental literacy learning strategies does the eye-tracking method reveal when assessing student behaviour at the learning centre’s exhibition? Research objective: to reveal the strategies used by students to perceive environmental content information at the science centre. Methodology, Methods, Research Instruments or Sources Used Twenty-sixth-grade students whose parents signed consent forms participated in the study. Students of this age are in the early stages of adolescence, when thinking transitions from concrete to formal operations (Piaget, 2002). This means that they begin to see the causes and consequences of phenomena and possible scenarios; abstract thinking intensifies as students deepen their understanding of information through scientific language and symbols, and new patterns of thinking emerge. These developmental processes require educators to ensure a wide variety of meaningful learning experiences, so that a visit to a science centre is not just an entertaining experience. Therefore, it is important to analyse how 6th-grade students perceive the science centre’s exhibitions and the natural science literacy they promote. Data was collected using eye-tracking technology. The study was conducted at the Science Island science centre (Kaunas, Lithuania). Data were collected using Tobii Glasses3 eye-tracking technology and a semi-structured interview method. The eye-tracking procedure with each student lasted about 2–7 minutes at each stand. The average interview duration was 12 minutes. During the interview, students described their learning strategy at the science centre exhibit and answered other questions. A semi-structured interview was chosen to gather detailed information on the impact of the science centre’s activities on students' science literacy. Methods of analysis of research data: eye-tracking data were analysed using the snapshot function; fixations were projected onto images of scientific objects, areas of interest (AOIs), and transitions were described. The distribution of attention between marked AOIs (points of interest) was visualized using sequence trajectories (Popelka & Vyslouzil, 2025). The data from the student interviews were analysed using qualitative thematic analysis. The students' responses were transcribed, key quotations were selected, sub-themes were formulated, and these sub-themes were combined into themes using a deductive approach grounded in an analysis of the scientific literature (Braun & Clarke, 2006). Conclusions, Expected Outcomes or Findings The study's results directly reflect visitors' individual learning strategies, as students interact differently with the same textual or visual exhibits, thereby allowing conclusions to be drawn about their information-processing methods and strategies for interacting with the exhibition. These data allow us to determine students' cognitive load, the quality of their experience at the science centre, the nature of the teacher's role, and the structures of learning activities, showing how different forms of artifacts help or hinder the processing of environmental content. Thematic analysis of the student interview data revealed the following main themes: environmental literacy, learning experiences at the science centre, student engagement, and the role of the teacher. The exhibits at the science centre demonstrated their educational potential for 6th-grade students by fostering environmental literacy through the study of environmental safety topics, including air pollution and climate change. However, students spend little time at some exhibits, tend to experiment first, focus their attention on the activity itself rather than on the educational content or learning objectives presented, and read the instructions or explanations only just before leaving the exhibit, often ignoring important information. Based on the results, recommendations were formulated for science centre staff on how to increase students' interest in the exhibits. The research data can contribute to improving the environmental literacy of European students and, from the perspective of Lithuanian students, to maintaining stable student achievement results, as was achieved in the PISA 2022 study, when Lithuania was included in a very narrow group of countries with high resilience and managed to ensure a holistic approach, focusing not only on knowledge but also on the emotional state and cooperation of students, which helps the education system remain stable and functional even in extreme conditions. References Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. Davidson, J., Jones, C., Johnson, M., Yildiz, D., & Prahalad, V. (2023). Renewing the purpose of geography education: Eco‐anxiety, powerful knowledge, and pathways for transformation. Geographical Research, 61(4), 429–442. Eren-Şişman, E. N., Çiğdemoğlu, C., Kanlı, U., & Köseoğlu, F. (2020). Science teachers’ professional development about science centers: Enhancing science teachers’ views concerning nature of science. Science & Education, 29(5), 1255–1290. Kervinen, A., Roth, W. M., Juuti, K., & Uitto, A. (2020). The resurgence of everyday experiences in school science learning activities. Cultural Studies of Science Education, 15(4), 1019–1045. DOI:10.1007/s11422-019-09968-1 Kontkanen, S., Koskela, T., Kanerva, O., Kärkkäinen, S., Waltzer, K., Mikkilä-Erdmann, M., & Havu-Nuutinen, S. (2024). Science capital as a lens for studying science aspirations – a systematic review. Studies in Science Education, 61(1), 89–115. Krogh-Jespersen, S., Quinn, K. A., Krenxer, W. L. D., Nguyen, C., Greenslit, J., & Price, A. (2020). Exploring the awe-some: Mobile eye-tracking insights into awe in a science museum. PLoS ONE, 15(9), e0239204. Larsen, T. B. (2024). Celebrating progress in geography education: NCGE’s ongoing role in shaping the future of geography. The Geography Teacher, 21(4), 146–147. Magnussen, R., Zachariassen, M., Kharlamov, N., & Larsen, B. (2017). Mobile eye tracking methodology in informal E-learning in social groups in technology-enhanced science centres. Electronic Journal of E-Learning, 15(1), 46–58. Martín-García, J., & Dies Álvarez, M. E. (2024). Beyond the walls of formality: the role of non-formal science activities in teachers’ professional development. Asia-Pacific Journal of Teacher Education, 52(2), 207–225. Osborne, J., & Allchin, D. (2025). Science literacy in the twenty-first century: informed trust and the competent outsider. International Journal of Science Education, 47(15–16), 2134–2155. Popelka, S., & Vyslouzil, J. (2025, May). Understanding Visitor Behavior in Geographic Exhibit with Eye-Tracking. In Proceedings of the 2025 Symposium on Eye Tracking Research and Applications (pp. 1–7). Teo, T. W., Loh, Z. H. J., Kee, L. E., Soh, G., & Wambeck, E. (2024). Mediational affordances at a science centre gallery: an exploratory and small study using eye-tracking and interviews. Research in Science Education, 54(4), 775–795. Valladares, L. (2021). Scientific literacy and social transformation: Critical perspectives about science participation and emancipation. Science & Education, 30(3), 557–587. Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). Academic Press. | ||