Computational Thinking: What Should Our Students Know And Be Able To Do?
- Conference
- Location
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Louisville, Kentucky
- Publication Date
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June 20, 2010
- Start Date
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June 20, 2010
- End Date
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June 23, 2010
- ISSN
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2153-5965
- Conference Session
- Tagged Division
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Educational Research and Methods
- Page Count
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20
- Page Numbers
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15.302.1 - 15.302.20
- DOI
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10.18260/1-2--15877
- Permanent URL
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https://peer.asee.org/15877
- Download Count
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362
Paper Authors
Dianne Raubenheimer North Carolina State University
Eric Wiebe North Carolina State University
Dr. Eric Wiebe is an Associate Professor in the Department of Mathematics, Science, and Technology Education at NC State University. He received his Doctorate in Psychology and has focused much of his research on issues related to the use of technology in the instructional
environment. He has also worked on the integration of scientific visualization concepts and techniques into both secondary and post-secondary education. Dr. Wiebe has been a member of ASEE since 1989.
Chia-Lin Ho North Carolina State University
Chia-Lin Ho joined the Computing across Curricula Team in early 2008 as a research assistant.She is a graduate student in the Industrial/Organizational Psychology
Doctoral Program. She received a B.S. in Psychology and a Bachelor of Business Administration at the National Cheng-Chi University in Taiwan in 2002 and her Masters in I/O Psychology at the University of North Carolina at Charlotte in 2005. Her research interests include measurement and evaluation issues, individual differences, leadership, cross-cultural studies, work motivation, and the application of technology on human resources management.
Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract
Computational thinking: What should our students know and be able to do? Abstract
A NSF funded project on our campus has two overarching goals: (1) to create a computational thinking thread in engineering programs that spans from the freshman to senior years and bridges the divide between freshman year computing and computing in upper-level classes, and (2) to enable students to take computing competencies to the next level, where they are able to perform high-level computing tasks within the context of a discipline.
To achieve the goals of the project, faculty fellows from different engineering departments participate in a series of seminars relating to computational thinking that are held over the duration of a semester. The faculty fellows also undertake action research projects in their classrooms as they redesign course curricula to integrate computational thinking skills. In order to build relevant curricula and to offer appropriate faculty development sessions, it was first necessary to identify what computational skills and competencies different engineering industries expect of graduates as they enter the workforce and in their first years on the job. This presentation will share the results of the data collection and analysis effort centered on identifying these criteria.
The starting point for identifying industry needs was a workshop held with a panel of industry representatives. Based on the results of the industry workshop, a model of computational capabilities emerged that articulated different levels of computational ability in a problem solving context. Using this framework, a Delphi process was employed to survey a group of practicing engineers employed by companies hiring graduates from our university, to gain consensus about desired computational skills and competencies. In the first round of the Delphi, six open-ended questions were posed. Preliminary versions of the questions were piloted at the industry panel workshop and refined based on the framework for use in the Delphi study. The open-ended responses were coded by three researchers independently and then collectively developed into a consensus coding scheme. The resulting coded responses clustered into five main themes, with interrelationships established between primary themes and subthemes. Using these themes, the second round Delphi survey was developed requesting the same employers to rate the importance of computational skills on a 5-point scale from 'not important' to 'very important'.
In addition to presenting results of both rounds of the Delphi study and the model of computational abilities, we will present the pre- and post-course student survey results conducted in classes where curriculum changes have been piloted based on this model of computational thinking. The purpose of the student surveys was to find out if changes in the courses reflected the computational skills highlighted by industry representatives as essential skills for graduates to possess.
Finally, we will present recommendations for larger scale curricular changes in the different engineering disciplines based on the findings from this study.
Raubenheimer, D., & Wiebe, E., & Ho, C. (2010, June), Computational Thinking: What Should Our Students Know And Be Able To Do? Paper presented at 2010 Annual Conference & Exposition, Louisville, Kentucky. 10.18260/1-2--15877
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