Studying Your Students as They Learn: A Case Study of CAD Education

Abstract

Having observed mechanical engineering seniors at the American University of Beirut (AUB) go about learning computer-aided design (CAD) in a formal setting, the instructors always wondered why some students acquire CAD skills with relative ease while some others seem to struggle. For this reason, a methodical study was launched in order to address this issue. Hence, and in order to “study the students as they learn” was accomplished by following 74 mechanical engineering seniors (it took three academic years including AY 2008–09 in order to have access to this relatively large number of trainees) as they went through a semester-long formal training on a commercial computer-aided design (CAD) package (Pro/Engineer, version Wildfire). The study methodically explored the trainees’: (1) technical background, (2) behavioral attributes (willingness-to-learn), and their (3) learning preferences. Investigating the technical background included quantifying the trainees’ relevant technical competencies specifically: basic math foundation, advanced math foundation, CAD-related mathematical foundation, computer science and engineering foundation, methodologies related to CAD, graphics foundation, and mechanical design foundation. Determining the trainees’ behavioral attributes included exploring their initial attitude towards learning of CAD, perception and imagination, and gauging their actual behavior (practice and CAD skills learned) throughout the training. Trainees’ learning styles were determined according to the index of learning styles, ILS [1]. Furthermore, and in order to assess the trainees’ progress in CAD knowledge acquisition, competency tests were conducted at four intervals throughout the semester-long study (2, 4, 7, and 12 weeks). The assessment involved hands-on building of CAD test parts of comparable complexity. At the conclusion of the study, statistical methods were used to correlate the trainees’ attributes with their monitored performance. Only a fraction (17 out of a class of 74 trainees or about one in four) of the trainees were found to fit the “star CAD trainee” mold which was defined in this study as someone who is fast on the tube as well as perceptive enough to be see through the procedure of building progressively more sophisticated CAD models. A profile of this “star CAD trainee” character emerges as an individual who is technically competent and perceptive, with personal drive and positive attitude, and who possesses active, sensor, sequential and visualizing learning styles.