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

Abstract

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.

Comparing the Visual Perception According to the Performance Using the Eye-Tracking Technology in High-Fidelity Simulation Settings

“…Results showed that experts watched the tools for a shorter time and the ball for a longer time than novices did [ 22 ]. The eye-tracking technology allowed the distinctions in visual perception of the experts and novices [ 23 , 24 , 25 , 26 ]. Typically, novice clinicians tend to unnecessarily activate data-collection approach to validate their hypothesis before arriving at a final diagnosis while experts make appropriate assumptions more quickly based on past similar experiences and accurately perceive more precisely the relative importance of information such as case progression, vital signs, and symptoms [ 27 ].…”

Oral presentation assessment and image reading behaviour on brain computed tomography reading in novice clinical learners: an eye-tracking study

“…Visual attention was measured in terms of eye movement, including DT and FC. The reason why DT and FC were used is that they have shown potential in detecting cognitive processes during visual search, especially in problem-solving analysis [ 20 , 21 ]. In contrast to measuring mean tendency of visual attention, the LSA [ 22 ], LMMs, and TE were used to explore the distribution of attention on the AOIs, as well as temporal relationships among AOIs (Fig.…”

I see something you do not: Eye movement modelling examples do not improve anomaly detection in interpreting medical images

“…The didactic explanations can be adapted to the level of learners and make them more understandable for the learner (Isaacs & Clark, 1987). Additionally, the eye movements of experts became more similar to novices when behaving didactically (Emhardt et al, 2020). The authors argue that this behaviour may facilitate following the experts task solving behaviour for novices.…”