N. Gu, S. Watanabe, H. Erhan, M. Hank Haeusler, W. Huang, R. Sosa (eds.), Rethinking Comprehensive Design: Speculative Counterculture, Proceedings of the 19th International Conference on Computer- Aided Architectural Design Research in Asia CAADRIA 2014, 831–840. © 2014, The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong CONFRONTING THE CHALLENGES OF COMPUTATIONAL DESIGN INSTRUCTION NICHOLAS SENSKE University of North Carolina at Charlotte, Charlotte, NC, USA nsenske@uncc.edu Abstract. Many architects understand that learning to program can be a challenge, but assume that time and practice are the only barriers to performing well enough at it. However, research from computer sci- ence education does not support this assumption. Multinational studies of undergraduate computer science programs reveal that a significant number of students in their first and second year of full-time instruc- tion still have serious misconceptions about how computer programs work and an inability to design programs of their own. If computer science students have trouble learning to think and express themselves computationally, what does this say about architects' chances of learn- ing to program well? Moreover, if common problems have been iden- tified, can architectural educators learn anything from findings in computer science education research? In order to determine if this re- search is relevant to architecture, the author conducted a pilot study of architecture students consisting of program analysis and conceptual knowledge tests. The study found that student performance was poor in ways similar to those revealed in the computer science education research. Because architects face similar challenges as computer sci- ence majors, this suggests that the discipline could benefit from more investment in educational collaborations. In addition, empirical re- search – from architecture as well as other fields – must play a more substantial role in helping architects learn computational thinking and expression. Keywords. Computational design education; programming; computer science education research; empirical research 1. Introduction In recent years, computational methods, such as those found in BIM, genera- tive scripting, energy simulation, and environmental analysis, have moved