Exploring viewing behavior data from whole slide images to predict correctness of students' answers during practical...

The way of viewing whole slide images (WSI) can be tracked and analyzed. In particular, it can be useful to learn how medical students view WSIs during exams and how their viewing behavior is correlated with correctness of the answers they give. We used software-based view path tracking method that enabled gathering data about viewing behavior of multiple simultaneous WSI users. This approach was implemented and applied during two practical exams in oral pathology in 2012 (88 students) and 2013 (91 students), which were based on questions with attached WSIs. Gathered data were visualized and analyzed in multiple ways. As a part of extended analysis, we tried to use machine learning approaches to predict correctness of students' answers based on how they viewed WSIs. We compared the results of analyses for years 2012 and 2013 - done for a single question, for student groups, and for a set of questions. The overall patterns were generally consistent across these 3 years. Moreover, viewing behavior data appeared to have certain potential for predicting answers' correctness and some outcomes of machine learning approaches were in the right direction. However, general prediction results were not satisfactory in terms of precision and recall. Our work confirmed that the view path tracking method is useful for discovering viewing behavior of students analyzing WSIs. It provided multiple useful insights in this area, and general results of our analyses were consistent across two exams. On the other hand, predicting answers' correctness appeared to be a difficult task - students' answers seem to be often unpredictable.