An algorithmic approach to determine expertise development using object-related gaze pattern sequences

Eye tracking (ET) technology is increasingly utilized to quantify visual behavior in the study of the development of domain-specific expertise. However, the identification and measurement of distinct gaze patterns using traditional ET metrics has been challenging, and the insights gained shown to be inconclusive about the nature of expert gaze behavior. In this article, we introduce an algorithmic approach for the extraction of object-related gaze sequences and determine task-related expertise by investigating the development of gaze sequence patterns during a multi-trial study of a simplified airplane assembly task. We demonstrate the algorithm in a study where novice (n = 28) and expert (n = 2) eye movements were recorded in successive trials (n = 8), allowing us to verify whether similar patterns develop with increasing expertise. In the proposed approach, AOI sequences were transformed to string representation and processed using the k-mer method, a well-known method from the field of computational biology. Our results for expertise development suggest that basic tendencies are visible in traditional ET metrics, such as the fixation duration, but are much more evident for k-mers of k > 2. With increased on-task experience, the appearance of expert k-mer patterns in novice gaze sequences was shown to increase significantly (p < 0.001). The results illustrate that the multi-trial k-mer approach is suitable for revealing specific cognitive processes and can quantify learning progress using gaze patterns that include both spatial and temporal information, which could provide a valuable tool for novice training and expert assessment.

Exploring change in networks supporting the deliberate practice of popular musicians

Popular musicians are embedded in dynamic networks supporting their expertise development across different phases. During these phases, network actors support different aspects of deliberate practice in which a musician needs to engage to become an expert. Research in the domain of music is scarce in terms of investigating the change in the supportive networks of deliberate practice over time. Semi-structured interviews with five expert and five intermediate popular musicians were used to explore changes in networks supporting the deliberate practice during their childhood, apprenticeship, and career phases. Egocentric network analysis revealed that networks supporting the deliberate practice of expert musicians are more dynamic and less stable when considering the different phases than the networks of intermediates. In addition, experts are supported by a larger number of network actors during the developmental phases. In both groups, the number of network actors decreased as the musicians progressed through the phases. This decrease was more precipitous between the childhood and apprenticeship phases. Overall, expertise development as a popular musician depends not only on deliberate practice but also on the diversity and change in an adaptive support network from childhood to adulthood.

The Development of Music Expertise: Applications of the Theories of Deliberate Practice and Deliberate Play

Musicians and athletes share many common traits. Both groups learn a combination of physical and mental skills to attain expert status. In this literature review, I provide a short history of research on expertise development and two models: Bloom’s model of expertise development and the Developmental Model of Sport Participation. The Bloom model categorizes learning activities between combinations of free play and deliberate practice throughout the three stages of development. However, Developmental Model of Sport Participation includes a new category, deliberate play, which combines aspects of play and deliberate practice. Research indicating music learning through deliberate practice, deliberate play, and music play is presented. If students are able to learn through the more enjoyable deliberate play and music play, teachers should consider including these activities to better match developmental stages and potentially improve retention. Implications for future research and music teachers are discussed.

Expertise development in volumetric image interpretation of radiology residents: what do longitudinal scroll data reveal?

The current study used theories on expertise development (the holistic model of image perception and the information reduction hypothesis) as a starting point to identify and explore potentially relevant process measures to monitor and evaluate expertise development in radiology residency training. It is the first to examine expertise development in volumetric image interpretation (i.e., CT scans) within radiology residents using scroll data collected longitudinally over five years of residency training. Consistent with the holistic model of image perception, the percentage of time spent on full runs, i.e. scrolling through more than 50% of the CT-scan slices (global search), decreased within residents over residency training years. Furthermore, the percentage of time spent on question-relevant areas in the CT scans increased within residents over residency training years, consistent with the information reduction hypothesis. Second, we examined if scroll patterns can predict diagnostic accuracy. The percentage of time spent on full runs and the percentage of time spent on question-relevant areas did not predict diagnostic accuracy. Thus, although scroll patterns over training years are consistent with visual expertise theories, they could not be used as predictors of diagnostic accuracy in the current study. Therefore, the relation between scroll patterns and performance needs to be further examined, before process measures can be used to monitor and evaluate expertise development in radiology residency training.