Teaching machine learning to design students

23Citations
Citations of this article
20Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Machine learning is a key technology to design and create intelligent systems, products, and related services. Like many other design departments, we are faced with the challenge to teach machine learning to design students, who often do not have an inherent affinity towards technology. We successfully used the Embodied Intelligence method to teach machine learning to our students. By embodying the learning system into the Lego Mindstorm NXT platform we provide the student with a tangible tool to understand and interact with a learning system. The resulting behavior of the tangible machines in combination with the positive associations with the Lego system motivated all the students. The students with less technology affinity successfully completed the course, while the students with more technology affinity excelled towards solving advanced problems. We believe that our experiences may inform and guide other teachers that intend to teach machine learning, or other computer science related topics, to design students. © 2008 Springer-Verlag Berlin Heidelberg.

Author supplied keywords

Cite

CITATION STYLE

APA

Van Der Vlist, B., Van De Westelaken, R., Bartneck, C., Hu, J., Ahn, R., Barakova, E., … Feijs, L. (2008). Teaching machine learning to design students. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5093 LNCS, pp. 206–217). https://doi.org/10.1007/978-3-540-69736-7_23

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free