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Towards a Framework for Assessing Computational Competencies for Engineering Undergraduate Students

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Conference

2015 ASEE Annual Conference & Exposition

Location

Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015

ISBN

978-0-692-50180-1

ISSN

2153-5965

Conference Session

Measurement and Instrumentation

Tagged Division

Educational Research and Methods

Page Count

14

Page Numbers

26.1589.1 - 26.1589.14

DOI

10.18260/p.24925

Permanent URL

https://peer.asee.org/24925

Download Count

93

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Paper Authors

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Claudia Elena Vergara Michigan State University

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Claudia Elena Vergara is a Research Scientist in The Center for Engineering Education Research (CEER). She received her Ph.D. in Plant Biology from Purdue University. Her scholarly interests include: improvement of STEM teaching and learning processes in higher education, and institutional change strategies to address the problems and solutions of educational reforms considering the situational context of the participants involved in the reforms. She is involved in several research projects focusing on competencies- based curriculum redesign and implementation aimed to integration across curricula; increasing the retention rate of early engineering students; providing opportunities for STEM graduate students to have mentored teaching experiences.

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Michael Cavanaugh Michigan State University

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Subashini Nagendran Sivakumar Michigan State University

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Suba Nagendran Sivakumar is a Research Scientist in The Center for Engineering Education Research (CEER). She received her PhD in Plant Pathology from Michigan State University. Her scholarly interests include: research and teaching in Plant Pathology, Molecular Biology and improvement of STEM teaching and learning processes in higher education.

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Daina Briedis Michigan State University

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DAINA BRIEDIS is a faculty member in the Department of Chemical Engineering and Materials Science at Michigan State University and Assistant Dean for Student Advancement and Program Assessment in the College of Engineering. Dr. Briedis is involved in several areas of education research including student retention, curriculum redesign, and the use of technology in the classroom. She has been involved in NSF-funded research in the areas of integration of computation in engineering curricula and in developing comprehensive strategies to retain early engineering students. She is active nationally and internationally in engineering accreditation and is a Fellow of ABET and of the AIChE.

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Thomas David Dionise Michigan State University

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Abdol-Hossein Esfahanian Michigan State University

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Abdol-Hossein Esfahanian received his B.S. degree in Electrical Engineering and the M.S. degree in Computer, Information, and Control Engineering from the University of Michigan in 1975 and 1977 respectively, and the Ph.D. degree in Computer Science from Northwestern University in 1983. He was an Assistant Professor of Computer Science at Michigan State University from September 1983 to May 1990. Since June 1990, he has been an Associate Professor with the same department where he is currently serving as the Associate Chair. He was awarded ‘The 1998 Withrow Exceptional Service Award’, and ‘The 2005 Withrow Teaching Excellence Award’. Dr. Esfahanian has over 120 research papers including articles in journals such as IEEE Transactions, NETWORKS, Discrete Applied Mathematics, Graph Theory, and Parallel and Distributed Computing. He has developed a number of software packages for manipulation of graphs. He was an Associate Editor of NETWORKS, from 1996 to 1999. He has been conducting research in applied graph theory, computer communications, fault-tolerant computing, Information Technology, and data mining.

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Jon Sticklen Michigan Technological University

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Jon Sticklen is the chairperson of the Engineering Fundamentals Department, Michigan Technological University. In the decade of the 90s, Dr. Sticklen founded and led a computer science laboratory in knowledge-based systems in the College of Engineering, Michigan State University that focused on task specific approaches to problem solving, better known as expert systems. Over the last fifteen years, Dr. Sticklen has pursued engineering education research focused on early engineering with an emphasis on hybrid course design and problem-based learning. Dr. Sticklen assumed the chairperson of Engineering Fundamentals at Michigan Tech on August 1, 2014. His research has been supported by a number of companies, as well as by NSF/CISE, NSF/DUE. and DARPA. Specifically his research in DBER-based engineering education has been supported by NSF/DUE and NSF/CISE.

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Mark Urban-Lurain Michigan State University

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Mark Urban-Lurain is an Associate Professor and Interim Director of the Center for Engineering Education Research at Michigan State University.

Dr. Urban-Lurain is responsible for teaching, research and curriculum development, with emphasis on engineering education and, more broadly, STEM education.

His research interests are in theories of cognition, how these theories inform the design of instruction, how we might best design instructional technology within those frameworks, and how the research and development of instructional technologies can inform our theories of cognition. He is also interested in preparing future STEM faculty for teaching, incorporating instructional technology as part of instructional design, and STEM education improvement and reform.

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Abstract

Towards a Framework for Assessing Computational Competencies for Engineering Undergraduate StudentsAssessment is a central component of educational reform. Valid assessments are key tomeasuring student learning and further establish a relationship between instruction and learningoutcomes. Despite the central role that computation plays in engineering there remains anabsence of valid assessments to measure computational competencies for engineers. The focus ofthis paper is to describe our progress towards characterizing students’ skills and behaviorsassociated with computational competency as they solve engineering problems. This work willcontribute to our understanding about computational problem solving uniquely characterized inthe context of engineering.The Collaborative Process to Align Computing Education with Engineering Workforce Needs(CPACE) team developed a collaborative process between industry, business and academia toidentify the computational competencies and skills that are essential for a globally competitiveengineering workforce. These findings were translated to computer science (CS) concepts to beused in curricular implementation (CPACE computational competencies). Our goal was to infusecomputational problem solving competencies throughout the engineering undergraduatecurricula. To achieve this goal we introduced problems that provided a context where studentswere required to apply computational concepts for their solution.Our data collection involved student surveys and student artifacts including final project reportsand homework assignments. We designed rubrics based on the CPACE computationalcompetencies and used them to compare self-reported survey data regarding students’computational abilities and actual performance in classroom assignments. A major challengeemerged during initial analysis of student artifacts, we discovered that employing the artifactsalone made it difficult to recognize students’ computational thinking processes [let alonemeasure computational competencies] as they solved engineering problems. To complement ouranalysis and understand the complexity of the students’ computational thinking processes weconducted semi-structured interviews; the objective was to focus on the role of computationduring the problem solving process.The interviews focused on asking students to describe/recount their thought processes as theysolved the engineering problem. The addition of interview data and qualitative analysis to the existing data (surveys, student artifacts, rubrics) allowed for triangulation and in depth validity checks across data sources. The CPACE team has identified critical steps that allow us to make clear connections between students’ computational thinking processesCPACE Qualitative Process. and CPACE computationalThe boxes represent distinct competencies. The overall processsteps in the process; the arrows of Interview Coding andpoint to the connections between Alignment to CPACEsteps.Computational Competencies is summarized in the figure above.This paper focuses on the analyses of the students’ interviews and our efforts to define atriangulation process [across data sources] that will allow us to inform the core researchquestion: What are the features that broadly characterize the knowledge, skills and behaviorsassociated with computational competencies for undergraduate engineering students?

Vergara, C. E., & Cavanaugh, M., & Sivakumar, S. N., & Briedis, D., & Dionise, T. D., & Esfahanian, A., & Sticklen, J., & Urban-Lurain, M. (2015, June), Towards a Framework for Assessing Computational Competencies for Engineering Undergraduate Students Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24925

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