Abstract:

Software engineering has shown to provoke mixed feelings among students. Moreover, most notably students have different needs (e.g. learning strategies, prior knowledge), so that lecturers have to deal with heterogeneous classes. Based on the frameworks discussed in [1], we believe that software engineering education can profit from eye tracking data to meet the challenges of those heterogeneous classes. To be able to improve our teaching methods regarding to instructional design and to develop suitable learning scenarios, we have to analyze student behavior during class (e.g. during debugging, modeling, coding).

In order to provide an ecologically valid environment (in contrast to lab settings), we need a new kind of eye tracking laboratory in form of a classroom. Such classrooms allow time and effort savings, uniform experiment conditions, gaze feedback and collaborative scenarios. However, this leads to problems like, non-trivial infrastructure, organizational issues, inferior data quality and boosted participant interaction [2], [3], which we need to face.

To our knowledge there are at least two existing approaches for multi eye tracker setups [2], [3], which partly meet our use cases. We adapt the idea of a group study system of [2] and the real-time gaze sharing introduced by [3] for our setup and extend these approaches with our specific use cases.

To meet the heterogeneity of our students, eye tracking can be used in at least three ways: Analysis, scaffolding and collaboration. Students have different problem-solving strategies, visually evident in their reading behavior (e.g. code reading). Combined with students' artifacts we can identify potential needs and develop suitable scaffolds and tasks. Another possible use case to apply eye tracking is scaffolding, which could be a gaze share from an expert. Finally, mutual gaze perception could enhance collaboration during tasks such as pair programming.

We present a work in progress concept of an eye tracking classroom built on the experience of existing classroom like laboratories. The resulting infrastructure shall allow colleagues from all departments to harness the possibilities of the eye tracking classroom.

References:
[1] H. Jarodzka, K. Holmqvist, and H. Gruber, Eye tracking in Educational Science: Theoretical frameworks and research agendas, Journal of Eye Movement Research, vol. 10, no. 1, 2017, issn: 1995-8692. [Online]. Available: https://bop.unibe.ch/JEMR/article/download/2959/pdf-1013.
[2] M. Bielikova, M. Konopka, J. Simko, R. Moro, J. Tvarozek, P. Hlavac, and E. Kuric, Eye-tracking en masse: Group user studies, lab infrastructure, and practices, Journal of Eye Movement Research, vol. 11, no. 3, 2018, issn: 1995-8692. [Online]. Available:
https://bop.unibe.ch/JEMR/article/view/4184/Bielikova_etal_JEMR_11-3-6.
[3] M. Nyström, D. C. Niehorster, T. Cornelissen, and H. Garde, Real-time sharing of gaze data between multiple eye trackers-evaluation, tools, and advice, Behavior research methods, vol. 49, no. 4, pp. 1310-1322, 2017. doi: 10.3758/s13428-016-0806-1.

Keywords:

Eye Tracking, Software Engineering Education, Scaffolding.