Learning through the eyes of another

Over the past decade, rapid technological advancements and budget constraints have increased the de­mand for online education (Martin et al., 2020). Furthermore, the COVID-19 pandemic has vastly ac­cele­ra­ted this trend, compelling almost all education providers to migrate their courses to online learning platforms (Theelen & Van Breukelen, 2022). In view of other profound crises that affect mobility, such as climate change, political instabilities and future pandemics, it is safe to assume that online learning will remain in demand, even in a post-pandemic world ) (Bayne et al., 2020). In this context, while educational research has made significant progress in establishing design principles that ensure effective online teaching and learning, the main focus of this scholarly work is on the acquisition of declarative knowledge and cognitive skills. Moreover, since very little is known about the online teaching and distance learning of psychomotor skills (Kouhia et al., 2021; Lehtiniemi et al., 2023), this paper and exhibition explore how eye-tracking technology (ETT) creates unique opportunities to improve craft education in hybrid and distant learning settings

Rethinking Pedagogical Use of Eye Trackers for Visual Problems with Eye Gaze Interpretation Tasks

Eye tracking technology enables the visualisation of a problem solver's eye movement while working on a problem. The eye movement of experts has been used to draw attention to expert problem solving processes in a bid to teach procedural skills to learners. Such affordances appear as eye movement modelling examples (EMME) in the literature. This work intends to further this line of work by suggesting how eye gaze data can not only guide attention but also scaffold learning through constructive engagement with the problem solving process of another human. Inferring the models’ problem solving process, be it that of an expert or novice, from their eye gaze display would require a learner to make interpretations that are rooted in the knowledge elements relevant to such problem solving. Such tasks, if designed properly, are expected to probe or foster a deeper understanding of a topic as their solutions would require not only following the expert gaze to learn a particular skill, but also interpreting the solution process as evident from the gaze pattern of an expert or even of a novice. This position paper presents a case for such tasks, which we call eye gaze interpretation (EGI) tasks. We start with the theoretical background of these tasks, followed by a conceptual example and representation to elucidate the concept of EGI tasks. Thereafter, we discuss design considerations and pedagogical affordances, using a domain-specific (chemistry) spectral graph problem. Finally, we explore the possibilities and constraints of EGI tasks in various fields that require visual representations for problem solving

Strategic gaze: an interactive eye-tracking study

We present an interactive eye-tracking study that explores the strategic use of gaze. We analyze gaze behavior in an experiment with four simple games. The game can either be a competitive (hide & seek) game in which players want to be unpredictable, or a game of common interest in which players want to be predictable. Gaze is transmitted either in real time to another subject, or it is not transmitted and therefore non-strategic. We find that subjects are able to interpret non-strategic gaze, obtaining substantially higher payoffs than subjects who do not see gaze. If gaze is transmitted in real time, gaze becomes more informative in the common interest games and players predominantly succeed to coordinate on efficient outcomes. In contrast, gaze becomes less informative in the competitive game

Visualizing a Task Performer’s Gaze to Foster Observers’ Performance and Learning : a Systematic Literature Review on Eye Movement Modeling Examples

Eye movement modeling examples (EMMEs) are instructional videos (e.g., tutorials) that visualize another person’s gaze location while they demonstrate how to perform a task. This systematic literature review provides a detailed overview of studies on the effects of EMME to foster observers’ performance and learning and highlights their differences in EMME designs. Through a broad, systematic search on four relevant databases, we identified 72 EMME studies (78 experiments). First, we created an overview of the different study backgrounds. Studies most often taught tasks from the domains of sports/physical education, medicine, aviation, and STEM areas and had different rationales for displaying EMME. Next, we outlined how studies differed in terms of participant characteristics, task types, and the design of the EMME materials, which makes it hard to infer how these differences affect performance and learning. Third, we concluded that the vast majority of the experiments showed at least some positive effects of EMME during learning, on tests directly after learning, and tests after a delay. Finally, our results provide a first indication of which EMME characteristics may positively influence learning. Future research should start to more systematically examine the effects of specific EMME design choices for specific participant populations and task types

Eye(s) see what you do: The Role of Social Mechanisms in the Effectiveness of Eye Movement Modeling Examples as an Instructional Tool for Multimedia Learning

Learning with multimedia material (e.g. text and pictures) often leads to better learning outcomes than learning with text alone. However, it is challenging for learners to apply effective information processing strategies to benefit from multimedia materials for their learning success. Not all learners are capable of doing this without instructional support. Eye Movement Modeling Examples (EMME) support learners in internalising and applying effective multimedia processing strategies such as selection, organisation and integration. EMME consist of videos with recorded eye movements of an (expert) model illustrating the dynamic change of the eye movements of the model during the processing of the task material. Previous studies have shown a positive effect of EMME on the use of multimedia processing strategies as well as on learning outcomes. So far, however, the question of possible mechanisms underlying the effectiveness of EMME for multimedia learning has remained open. The present work therefore used two different approaches in three experiments to investigate the question of whether social mechanisms and factors play a role in the effectiveness of EMME. The first approach examined whether social mechanisms contribute to the efficacy of EMME beyond the effects of perceptual and (meta-) cognitive mechanisms. However, the results were not conclusive on this question. In a second approach, it was investigated whether social factors such as ( alleged) model-observer similarity and social comparison orientation can influence the effectiveness of EMME. Although the results for this approach provided first empirical evidence that social factors can influence the effectiveness of EMME, the overall picture was rather inconsistent. On the basis of the results of the three experiments it is therefore not possible to draw final conclusions about the role of social mechanisms and factors for the effectiveness of EMME. In summary, EMME can be an effective instructional support for multimedia learning. In addition, however, it was found that there are factors that can moderate the effectiveness of EMME.Lernen mit multimedialem Material (z. B. Text und Bild) führt häufig zu besseren Lernergebnissen als das Lernen mit Text allein. Es stellt Lernende jedoch vor die Herausforderung, geeignete Informationsverarbeitungsstrategien anzuwenden, um von multimedialen Materialien für ihren Lernerfolg zu profitieren. Hierzu sind nicht alle Lernenden ohne instruktionale Unterstützung in der Lage. Eye Movement Modeling Examples (EMME) unterstützen Lernende durch die Modellierung erfolgreicher multimedialer Verarbeitungsstrategien wie Selektion, Organisation und Integration dabei, diese zu internalisieren und anzuwenden. EMME bestehen aus Videos mit aufgezeichneten Blickbewegungen eines (Experten-) Modells, die die dynamische Veränderung des Blickverhaltens des Modells bei der Verarbeitung des Aufgabematerials zeigen. Bisherige Studien zeigen weitestgehend einen positiven Effekt von EMME sowohl auf die Nutzung multimedialer Verarbeitungsstrategien als auch auf die Lernergebnisse. Bislang blieb jedoch die Frage nach möglichen Mechanismen, die der Wirksamkeit von EMME für multimediales Lernen zugrunde liegen, offen. Die vorliegende Arbeit untersuchte daher mithilfe von zwei verschiedenen Ansätzen in drei Experimenten die Frage, ob soziale Mechanismen und Faktoren eine Rolle für die Wirksamkeit von EMME spielen. In einem ersten Ansatz wurde untersucht, ob soziale Mechanismen über die Wirkung von perzeptuellen und (meta-) kognitiven Mechanismen hinaus zur Wirksamkeit von EMME beitragen. Die Ergebnisse waren in Hinblick auf diese Frage jedoch nicht eindeutig. In einem zweiten Ansatz wurde untersucht, ob soziale Faktoren wie (vermeintliche) Modell-Beobachterähnlichkeit und soziale Vergleichsorientierung die Wirksamkeit von EMME beeinflussen können. Auch wenn die Ergebnisse für diesen Ansatz erste empirische Hinweise lieferten, dass soziale Faktoren die Effektivität von EMME beeinflussen können, zeigte sich insgesamt ein eher inkonsistentes Bild. Auf Basis der Ergebnisse der drei Experimente ist es daher nicht möglich, endgültige Schlussfolgerungen über die Rolle sozialer Mechanismen und Faktoren für die Wirksamkeit von EMME zu ziehen. Zusammenfassend zeigte sich, dass EMME eine wirksame instruktionale Unterstützung für multimediales Lernen sein können. Darüber hinaus zeigte sich jedoch auch, dass es Faktoren gibt, die die Effektivität von EMME moderieren können