Abstract
In undergraduate practical courses, it is common to work with groups of 100 or more students. These large-scale courses bring their own challenges. For example, course problems are too small and lack "the big picture"; grading becomes burdensome and repetitive for the teaching staff; and it is difficult to detect cheating. Based on their experience with a traditional large-scale practical course in image processing, the authors developed a novel course approach to teaching "Introduction to Digital Image Processing" (or EDBV, from the German course title Einführung in die Digitale Bild-Verarbeitung) for all undergraduate students of media informatics and visual computing and medical informatics at the TU Wien.
Reference
Artner, N. M., Janusch, I., & Kropatsch, W. G. (2015). Evaluating and Grading Students in Large-Scale Image Processing Lectures. IEEE Computer Graphics and Applications, 35(5), 101-c3. https://doi.org/10.1109/mcg.2015.107