Assessing an Adaptive Expertise Instrument in Computer-aided Design (CAD) Courses at Two Campuses

Abstract

In today's highly competitive market, CAD tools are widely used and thought to reduce time to market and increase engineering productivity. However, to take advantage of these putative benefits requires proper use of CAD tools. Merely teaching declarative knowledge (particular keystrokes and button picks) in CAD is not sufficient; students should acquire deeper procedural knowledge (design strategy) in CAD. This will allow them to gain a level of expertise that is adaptive in nature. Recent research in engineering education finds that experts demonstrate two distinct characteristics: adaptive versus routine expertise. Adaptive experts possess the content knowledge similar to routine experts in the field, but also the ability to effectively utilize and extend their content knowledge. Epistemological beliefs, metacognitive skills, multiple perspectives, and learning orientations are among the constructs that can define adaptive expertise. This work describes the implementation of an instrument used to measure adaptive expertise in two courses at two universities. The instrument contains questions covering four dimensions: multiple perspectives, meta-cognitive self-assessment, goals and beliefs, and epistemology. In one university setting, freshmen and sophomore engineering students were surveyed with the instrument; in the other, junior and senior level engineering students were surveyed. In addition to the student participants, practicing engineers from industry were surveyed using the instrument. Participant demographic, education, and engineering experience data were collected. These data were used to examine the relationships among expertise related responses and demographic variables. We report the factor analyses results and the reliability coefficients of the instrument and the observed differences between students' and engineers' responses to survey items.

Computer-Aided Drawing Learning Method to Improve Students’ Cognitive and Psychomotor Aspects in Computer-Aided Drawing Competence

“…Learning CAD requires cognitive understandings. The importance of this cognitive aspect is corroborated by Johnson, Ozturk and Yalvac et al (2012) that "cognitive skills are critical for effective use of modern CAD programs". This implies that in CAD learning, there is not one standard and rigid way to solve a technical problem.…”

“…Flavell argues that metacognitive is the internal processing that makes use of cognitive strategies to monitor and control other learning and memory processes ". In addition, Johnson, Ozturk and Yalvac et al (2012) argue on the importance of developing CAD learning by focusing on the metacognitive aspect (Gagne, Briggs and Wager, 1992: 71).…”

Boosting computer‐aided design pedagogy using interactive self‐assessment graphical tools

“…Computer‐aided design (CAD) tools have gained great relevance in reinforcing students' education in engineering studies, as it allows them to implement and check technical drawings in a fast and efficient way [18, 21, 34]. However, most CAD teaching techniques comprise the presentation of the main programme commands, and the implementation of specific tutorials [38, 48], which are not enough to evaluate a student's ability to manage CAD programmes. Engineering students could use CAD tools to solve almost any engineering problem [37].…”

Measuring adaptiveness among college students and working professionals

“…Johnson et al [14] confirmed the reliability of the survey tool developed by Fisher and Peterson in a 2012 study, although low participation rates of various sub-populations reduces the ability to make comparisons. Pierrakos et al [15] also performed a study examining the reliability of the survey tool and again, found it to be a reliable instrument, in addition to showing differences in AE levels displayed by senior students in two design programs, one of which was designed to teach adaptive expertise and included mastery-based learning as well as "Explicit Values of the Course being grit, metacognition, innovation, collaboration, and quality".…”