Deep learning stimulated

Abstract

Teaching manufacturing techniques to 250 bachelor level industrial design engineering students is not straightforward, especially when a fair amount of abstraction is required. Our students find it difficult to grasp abstract matters through a textbook, even when they have lectures delivered by co-authors of the book. We found that students avoided putting their brains to work early-on in the 10-week course, and then faced difficulty nearing the final exam. To overcome this, we encouraged students to come prepared to workshops, where they completed a selection of the textbook exercises under staff guidance. Initially this worked well. Over the years though, as the elaborations of those exercises were shared online, student attendance dropped, despite the available and inviting staff. What more could we do? A solution was found in changing the activities performed by the students. Inspired by Kuttenkeuler and Edström1, their concept of ‘time-on-task’ was tried in our education practice. A small part of the grade for theory was earned during the workshops, based on a reward system for delivering a convincing presentation of exercises on the topic at hand. It proved that this method made students come better prepared, in bigger numbers and with a remarkable positive impact on their final exam success rate.