Feeding a monster or doing good? Mining Industrial Design Student Feedback at Large

Abstract

In this paper, we describe work in progress, a study of a large database of written university teacher feedback given to Industrial Design students throughout the semester, over several years. This large corpus is captured technically in a database, but conceptually organized into several feedback moments per semester, which will be analyzed using a newly developed framework targeting Industrial Design education at the university level. Essential aspects of this paper focus on the translation of related work in the area of feedback mechanisms for higher education into a tailored framework for feedback in the area of Industrial Design, and the translation of the existing corpus of data into indicators of feedback quality and how feedback is received and further on used by students in their learning process. Outcomes will be used to further investigate how the quality of feedback evolves and to develop better tools for feedback. With this paper we aim at opening the discussion about our intended process and methodology, as well as inspiration for aspects we have missed so far.