Elif Ozturk
Texas A&M University
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Featured researches published by Elif Ozturk.
Computer-aided Design and Applications | 2014
Xiaobo Peng; Prentiss McGary; Elif Ozturk; Bugrahan Yalvac; Michael D. Johnson; Lauralee Valverde
The fast changing pace of modern CAD tools has demanded the users to be more adaptive to apply their CAD skills. This paper presents the initial work to transform adaptive expertise in the CAD education. An adaptive expertise survey (AES) and a contextual exercise were implemented in a freshman CAD class. The students’ responses to the survey and interviews were analyzed. The CAD models were evaluated based on the attributes. The statistically significant relationships among the variables are reported. The analyses examined the role of adaptive expertise in CAD modeling and the role of learner-centered contextual exercises on CAD modeling procedures. The findings suggest some differences between the students’ demographics and their adaptive expertise characteristics and positive effect of the contextual exercise on students’ CAD modeling procedures.
ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference | 2013
Michael D. Johnson; Elif Ozturk; Lauralee Valverde; Bugrahan Yalvac; Prentiss McGary; Xiaobo Peng
Computer-aided design (CAD) tools play a significant role in the modern product commercialization environment. As CAD and general CAx technology advances, it becomes more important to understand how engineers adapt their expertise to new environments and problems. This work examines a methodology consisting of a set of surveys, interviews, and exercises with a small group of practicing engineers to assess adaptive expertise (AE) and relate this AE to CAD modeling performance and procedures. Results detail AE survey results, a modeling and alteration exercise, and an exercise where engineers are asked to model a component using a CAD platform they are unfamiliar with. Interview and time use (from screen capture videos) results from this exercise are presented along with other data. Correlations among AE survey and interview variables and model analysis variables are presented. The epistemology dimension of the AE survey was found to be negatively correlated with both original modeling and alteration time. Overall modeling time in the different platform was positively correlated with the percentage of time a participant spent engaging in trial and error; modeling time in the different platform was negatively correlated with percentage of time spent doing actual modeling and the time spent thinking.Copyright
Computer-aided Design and Applications | 2015
Ke Liu; Xiaobo Peng; Prentiss McGary; Bugrahan Yalvac; Elif Ozturk; Michael D. Johnson; Lauralee Valverde
ABSTRACTThe authors have implemented a series of contextual CAD modeling exercises in a freshman CAD class to transform adaptive expertise in the CAD education. The students were interviewed before and after the exercises to capture their manifestation of adaptive expertise. At the end of semester, a CAD modeling test was given to the students. The CAD modeling procedures were evaluated based on the model attributes and students’ screen-recordings. The data analyses examine the role of learner-centered contextual exercise in CAD modeling process, and the correlations between the adaptive expertise in CAD modeling procedure. The findings show that the contextual exercises have positive effects on improving students’ adaptive expertise and CAD skills.
international conference on human-computer interaction | 2013
Michael D. Johnson; Elif Ozturk; Lauralee Valverde; Bugrahan Yalvac; Xiaobo Peng
As computer-aided design (CAD) tools become more integral in the product commercialization process, ensuring that students have efficient and innovative expertise necessary to adapt becomes more important. This work examines the role of adaptive expertise on CAD modeling behavior and the effect of contextual modeling exercises on the manifestation of behaviors associated with adaptive expertise in a population of student participants. A methodology comprising multiple data elicitation tools is used to examine these relationships; these tools include: survey data, model screen capture data analysis, and interviews. Results show that participants engaged in contextual exercises spent more of their modeling time engaged in actual modeling activities as opposed to planning when compared to a control group. Limited statistical support is provided for the role of contextual exercises leading to the manifestation of behaviors associated with adaptive expertise. The amount of time spent engaged in actual modeling is positively correlated with the adaptive expertise behaviors identified in the interviews.
ASME 2015 International Mechanical Engineering Congress and Exposition | 2015
Michael D. Johnson; Elif Ozturk; Bugrahan Yalvac; Lauralee Valverde; Xiaobo Peng; Ke Liu
Computer-aided design (CAD) tools are critical in the current fast-paced digital product commercialization environment. As firms move towards a model based enterprise, it becomes more important for engineers to develop the skills necessary to efficiently and effectively model components in CAD. The status of CAD education and training has often been decried as focusing too much on declarative knowledge, namely how to do specific procedures in a specific software program. This is opposed to the strategic knowledge or expertise that is adaptable to other CAD programs. To better inform CAD education and modeling procedures, an understanding of how experts model and model in novel situations is presented. Specifically, and novel to this work, the adaptive nature of these practicing professional’s CAD expertise is examined and compared to that of relatively novice students. The methods comprise a combination of screen capture data, model attributes, and the results of interviews to assess adaptive expertise.Practicing engineers are found to spend a smaller percentage of their modeling time engaged in actual modeling procedures (doing time). Significant differences related to model attributes include: practicing engineers being less likely to use pattern features, more likely to have incorrect feature terminations, and more likely to use more complex features (as measured by feature density). Results show practicing engineers as less likely to highlight strategies related to adaptive expertise prior to the modeling activity. Post interview results show practicing engineers with more manifestations of adaptive expertise. These results are in agreement with previous literature examining both general and CAD modeling expertise.Copyright
2015 ASEE Annual Conference & Exposition | 2015
Elif Ozturk; Bugrahan Yalvac; Michael L. Johnson
2014 ASEE Annual Conference & Exposition | 2014
Michael L. Johnson; Xiaobo Peng; Bugrahan Yalvac; Elif Ozturk; Ke Liu
2013 ASEE Annual Conference & Exposition | 2013
Elif Ozturk; Bugrahan Yalvac; Xiaobo Peng; Prentiss McGary; Michael L. Johnson
Archive | 2012
Michael L. Johnson; Michael D. Johnson; Elif Ozturk; Bugrahan Yalvac; Xiaobo Peng
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education | 2012
Elif Ozturk; Canan E. Unlu