@misc{GegenfurtnerBoucheixGruberetal., author = {Gegenfurtner, Andreas and Boucheix, Jean-Michel and Gruber, Hans and Hauser, Florian and Lehtinen, Erno and Lowe, Richard K.}, title = {Der Gaze Relational Index als Indikator visueller Expertise}, series = {51. Kongress der Deutschen Gesellschaft f{\"u}r Psychologie : 15. bis 20. September 2018, Goethe-Universit{\"a}t Frankfurt am Main, Campus Westend}, journal = {51. Kongress der Deutschen Gesellschaft f{\"u}r Psychologie : 15. bis 20. September 2018, Goethe-Universit{\"a}t Frankfurt am Main, Campus Westend}, issn = {2573-2773}, pages = {402}, abstract = {Eye tracking is a powerful technique that helps reveal how people process visual information. This paper discusses a novel metric for indicating expertise in visual information processing. Named the Gaze Relational Index (GRI), this metric is defined as the ratio of mean fixation duration to fixation count. Data from two eye-tracking studies of professional vision and visual expertise in using 3D dynamic medical visualizations are presented as cases to illustrate the suitability and additional benefits of the GRI. Calculated values of the GRI were higher for novices than for experts, and higher in non-representative, semi-familiar / unfamiliar task conditions than in domain-representative familiar tasks. These differences in GRI suggest that, compared to novices, experts engaged in more knowledge-driven, top-down processing that was characterized by quick, exploratory visual search. We discuss future research aiming to replicate the GRI in professional domains with complex visual stimuli and to identify the moderating role of cognitive ability on GRI estimates.}, language = {de} } @inproceedings{GruberWolffMottoketal., author = {Gruber, Hans and Wolff, Christian and Mottok, J{\"u}rgen and Bazo, Alexander and Hauser, Florian and Schreistetter, Stefan}, title = {Tutorial on Software Engineering Education in Co-Located Multi-User Eye-Tracking-Environments}, series = {Proceedings of the 32nd IEEE Conference on Software Engineering Education and Training: Munich, November 2020}, booktitle = {Proceedings of the 32nd IEEE Conference on Software Engineering Education and Training: Munich, November 2020}, doi = {10.1109/CSEET49119.2020.9206170}, abstract = {We briefly describe a tutorial on the application of Eye-Tracking technology for Software Engineering Education. We will showcase our setup of a large-scale Eye-Tracking-Classroom and its usage for real-time improvement of traditional learning scenarios in Software Engineering Education. We will focus on the integration of gaze data into modern integrated development environments (IDEs) and demonstrate a complete workflow for its usage in co-located multi-user Eye-Tracking-Environments.}, language = {en} } @inproceedings{HauserSchreistetterReuteretal., author = {Hauser, Florian and Schreistetter, Stefan and Reuter, Rebecca and Mottok, J{\"u}rgen and Gruber, Hans and Holmqvist, Kenneth and Schorr, Nick}, title = {Code reviews in C++: Preliminary results from an eye tracking study}, series = {ETRA '20 Short Papers: ACM Symposium on Eye Tracking Research and ApplicationsJune 2020}, booktitle = {ETRA '20 Short Papers: ACM Symposium on Eye Tracking Research and ApplicationsJune 2020}, isbn = {ISBN 9781450371346}, doi = {10.1145/3379156.3391980}, pages = {1 -- 5}, abstract = {Code reviews are an essential part of quality assurance in modern software projects. But despite their great importance, they are still carried out in a way that relies on human skills and decisions. During the last decade, there have been several publications on code reviews using eye tracking as a method, but only a few studies have focused on the performance differences between experts and novices. To get a deeper understanding of these differences, the following experiment was developed: This study surveys expertise-related differences in experts', advanced programmers', and novices' eye movements during the review of eight short C++ code examples, including correct and erroneous codes. A sample of 35 participants (21 novices, 14 advanced and expert programmers) were recruited. A Tobii Spectrum 600 was used for the data collection. Measures included participants' eye movements during the code review, demographic background data, and cued retrospective verbal comments on replays of their own eye movement recordings. Preliminary results give proof for experience-related differences between participants. Advanced and expert programmers performed significantly better in case of error detection and the eye tracking data implies a more efficient reviewing strategy.}, language = {en} } @inproceedings{HauserStarkMottoketal., author = {Hauser, Florian and Stark, Theresa and Mottok, J{\"u}rgen and Gruber, Hans and Reuter, Rebecca}, title = {Deliberate Practice in Programming: How is it carried out by programmers?}, series = {ECSEE '20: Proceedings of the 4th European Conference on Software Engineering Education, Seeon, Germany, June 2020}, booktitle = {ECSEE '20: Proceedings of the 4th European Conference on Software Engineering Education, Seeon, Germany, June 2020}, isbn = {ISBN 9781450377522}, doi = {10.1145/3396802.3396815}, pages = {42 -- 46}, abstract = {This work in progress study examines through which activities programmers perform deliberate practice to improve their own skills in coding and programming. For this reason, a qualitative questionnaire was developed and conducted with a sample of 22 participants. The results indicate that programmers perform formal and informal forms of training and learning. Typically, a classical programming training in the context of a university course or for work-related reasons is a first step in the acquisition of expertise. Building on these basic skills, non-formal and informal learning activities are carried out by the learners. Especially the social interaction and the collaborative work with other programmers is of great importance in this context. The activities mentioned by the test persons fulfil the characteristics of deliberate practice and will be examined more closely in a further study.}, language = {en} } @article{GegenfurtnerBoucheixGruberetal., author = {Gegenfurtner, Andreas and Boucheix, Jean-Michel and Gruber, Hans and Hauser, Florian and Lehtinen, Erno and Lowe, Richard K.}, title = {The gaze relational index as a measure of visual expertise}, series = {Journal of Expertise}, volume = {3}, journal = {Journal of Expertise}, number = {March}, publisher = {Michigan State University}, issn = {2573-2773}, pages = {32 -- 40}, abstract = {Eye tracking is a powerful technique that helps reveal how people process visual information. This paper discusses a novel metric for indicating expertise in visual information processing. Named the Gaze Relational Index (GRI), this metric is defined as the ratio of mean fixation duration to fixation count. Data from two eye-tracking studies of professional vision and visual expertise in using 3D dynamic medical visualizations are presented as cases to illustrate the suitability and additional benefits of the GRI. Calculated values of the GRI were higher for novices than for experts, and higher in non-representative, semi-familiar / unfamiliar task conditions than in domain-representative familiar tasks. These differences in GRI suggest that, compared to novices, experts engaged in more knowledge-driven, top-down processing that was characterized by quick, exploratory visual search. We discuss future research aiming to replicate the GRI in professional domains with complex visual stimuli and to identify the moderating role of cognitive ability on GRI estimates.}, language = {en} }