Seeing through a teacher's eyes improves students' imaging interpretation

Teaching through their eyes: effects on optometry teachers' adaptivity and students' learning when teachers see students' gaze

Adaptive teacher support fosters effective learning in one-to-one teaching sessions, which are a common way of learning complex visual tasks in the health sciences. Adaptive support is tailored to student needs, and this is difficult in complex visual tasks as visual problem-solving processes are covert and thus cannot be directly observed by the teacher. Eye-tracking apparatus can measure covert processes and make them visible in gaze displays: visualizations of where a student looks while executing a task. We investigate whether live dynamic gaze displays help teachers in being more adaptive to students' needs when teaching optical coherence tomography interpretation in one-to-one teaching sessions and whether this fosters learning. Forty-nine students and 10 teachers participated in a one-to-one teaching session in clinical optometry. In the control condition, teachers saw the learning task of the student and could discuss it with them, whereas in the gaze-display condition, teachers could additionally see where the student looked. After the 15-minute teaching session, a test was administered to examine achievement. Furthermore, students filled in the 'questionnaire on teacher support adaptivity', and teachers rated how adaptive their support was. Bayesian analyses provide some initial evidence that students did not experience support to be more adaptive in the gaze-display condition versus the control condition, nor were their post-test scores higher. Teachers rated their provided support as being more adaptive in the gaze-display versus the control condition. Further research could investigate if live dynamic gaze displays impact adaptive teaching when used over longer periods or with more teacher training.

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.

How Experts Adapt Their Gaze Behavior When Modeling a Task to Novices

Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem‐solving behavior as well as their eye movements to learners. While research on expert‐novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem‐solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.

A new way to look at simulation-based assessment: the relationship between gaze-tracking and exam performance

Objective

A key task of the team leader in a medical emergency is effective information gathering. Studying information gathering patterns is readily accomplished with the use of gaze-tracking glasses. This technology was used to generate hypotheses about the relationship between performance scores and expert-hypothesized visual areas of interest in residents across scenarios in simulated medical resuscitation examinations.

Methods

Emergency medicine residents wore gaze-tracking glasses during two simulation-based examinations (n=29 and 13 respectively). Blinded experts assessed video-recorded performances using a simulation performance assessment tool that has validity evidence in this context. The relationships between gaze patterns and performance scores were analyzed and potential hypotheses generated. Four scenarios were assessed in this study: diabetic ketoacidosis, bradycardia secondary to beta-blocker overdose, ruptured abdominal aortic aneurysm and metabolic acidosis caused by antifreeze ingestion.

Results

Specific gaze patterns were correlated with objective performance. High performers were more likely to fixate on task-relevant stimuli and appropriately ignore task-irrelevant stimuli compared with lower performers. For example, shorter latency to fixation on the vital signs in a case of diabetic ketoacidosis was positively correlated with performance (r=0.70, p<0.05). Conversely, total time spent fixating on lab values in a case of ruptured abdominal aortic aneurysm was negatively correlated with performance (r= −0.50, p<0.05).

Conclusions

There are differences between the visual patterns of high and low-performing residents. These findings may allow for better characterization of expertise development in resuscitation medicine and provide a framework for future study of visual behaviours in resuscitation cases.

Learning from where 'eye' remotely look or point: Impact on number line estimation error in adults

In this article, we present an investigation into the use of visual cues during number line estimation and their influence on cognitive processes for reducing number line estimation error. Participants completed a 0-1000 number line estimation task before and after a brief intervention in which they observed static-visual or dynamic-visual cues (control, anchor, gaze cursor, mouse cursor) and also made estimation marks to test effective number-target estimation. Results indicated that a significant pre-test to post-test reduction in estimation error was present for dynamic-visual cues of modelled eye-gaze and mouse cursor. However, there was no significant performance difference between pre- and post-test for the control or static anchor conditions. Findings are discussed in relation to the extent to which anchor points alone are meaningful in promoting successful segmentation of the number line and whether dynamic cues promote the utility of these locations in reducing error through attentional guidance.

The challenges of studying visual expertise in medical image diagnosis

CONTEXT

Visual expertise is the superior visual skill shown when executing domain-specific visual tasks. Understanding visual expertise is important in order to understand how the interpretation of medical images may be best learned and taught. In the context of this article, we focus on the visual skill of medical image diagnosis and, more specifically, on the methodological set-ups routinely used in visual expertise research.

METHODS

We offer a critique of commonly used methods and propose three challenges for future research to open up new avenues for studying characteristics of visual expertise in medical image diagnosis. The first challenge addresses theory development. Novel prospects in modelling visual expertise can emerge when we reflect on cognitive and socio-cultural epistemologies in visual expertise research, when we engage in statistical validations of existing theoretical assumptions and when we include social and socio-cultural processes in expertise development. The second challenge addresses the recording and analysis of longitudinal data. If we assume that the development of expertise is a long-term phenomenon, then it follows that future research can engage in advanced statistical modelling of longitudinal expertise data that extends the routine use of cross-sectional material through, for example, animations and dynamic visualisations of developmental data. The third challenge addresses the combination of methods. Alternatives to current practices can integrate qualitative and quantitative approaches in mixed-method designs, embrace relevant yet underused data sources and understand the need for multidisciplinary research teams.

CONCLUSION

Embracing alternative epistemological and methodological approaches for studying visual expertise can lead to a more balanced and robust future for understanding superior visual skills in medical image diagnosis as well as other medical fields.

An eye movement pre-training fosters the comprehension of processes and functions in technical systems

The main research goal of the present study was to investigate in how far pre-training eye movements can facilitate knowledge acquisition in multimedia (pre-training principle). We combined considerations from research on eye movement modeling and pre-training to design and test a non-verbal eye movement-based pre-training. Participants in the experimental condition watched an animated circle moving in close spatial resemblance to a static visualization of a solar plant accompanied by a narration in a subsequently presented learning environment. This training was expected to foster top-down processes as reflected in gaze behavior during the learning process and enhance knowledge acquisition. We compared two groups (N = 45): participants in the experimental condition received pre-training in a first step and processed the learning material in a second step, whereas the control group underwent the second step without any pre-training. The pre-training group outperformed the control group in their learning outcomes, particularly in knowledge about processes and functions of the solar plant. However, the superior learning outcomes in the pre-training group could not be explained by eye-movement patterns. Furthermore, the pre-training moderated the relationship between experienced stress and learning outcomes. In the control group, high stress levels hindered learning, which was not found for the pre-training group. On a delayed posttest participants were requested to draw a picture of the learning content. Despite a non-significant effect of training on the quality of drawings, the pre-training showed associations between learning outcomes at the first testing time and process-related aspects in the quality of their drawings. Overall, non-verbal pre-training is a successful instructional intervention to promote learning processes in novices although these processes did not directly reflect in learners' eye movement behavior during learning.