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Board 363: Promoting the Dispositional Dimension of Competency in Undergraduate Computing Programs

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Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

15

DOI

10.18260/1-2--43018

Permanent URL

https://peer.asee.org/43018

Download Count

110

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Paper Authors

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Bonnie Kathleen MacKellar St John's University

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Bonnie MacKellar is an associate professor of computer science at St John's University. Her research interests include semantic models in medical informatics, and software engineering education, including HFOSS, and the role of competencies in preparing students for careers in computing.

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Natalie Kiesler DIPF | Leibniz Institute for Research and Information in Education

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Natalie Kiesler completed her doctorate in Computer Science at Goethe University Frankfurt, Germany in 2022. The focus of her thesis was on modeling competencies and tutoring feedback for novice learners of programming. She is currently a senior researcher at the DIPF Leibniz Institute for Educational Research and Information in Frankfurt, Germany where she contributes to the development of an open research data infrastructure for qualitative research data. Dr. Kiesler's research interests include computing education, competency-based learning and teaching, feedback, and open science.

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Rajendra K. Raj Rochester Institute of Technology Orcid 16x16 orcid.org/0000-0003-2378-1068

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Rajendra K. Raj is a Professor of Computer Science at the Rochester Institute of Technology. His current research interests cover the nexus between data science and cybersecurity, as applied to a variety of domains including healthcare, finance, and critical infrastructure protections. His recent focus has been on improving student preparation for overall career success.

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Mihaela Sabin University of New Hampshire Orcid 16x16 orcid.org/0000-0003-1315-5151

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Mihaela Sabin has taught a variety of computing courses designed to facilitate learning activities that value students' diverse lived experiences. Her current research includes computing education and curriculum development, with emphasis on professional competencies and faculty role modeling. She has contributed to the AI field of constraint satisfaction with a new representational model based on conditional constraints. Sabin chaired the ACM/IEEE Computer Society IT2017 task group, who authored the “Curriculum Guidelines for Baccalaureate Degree Programs in Information Technology” report. She received external funding awards from the National Science Foundation, New Hampshire Innovation Research Center, Google for Education, and other private and corporate foundations for projects that support computing learning by students and teachers. Sabin serves on the ACM Education Board and on the ACM SIGITE Executive Committee as Vice-Chair for Education. She also represents SIGITE on the ACM Education Advisory Committee. She is a founding member of the Computer Science Teacher Association NH Chapter and of the CS4NH alliance. Sabin is an ABET Program Evaluator, a member of the ABET CS Accreditation Board, and a member of the ABET CAC/CSAB Diversity, Equity, and Inclusion committee. Sabin's top priority professionally and personally is to bring the quality of human being into computing as a discipline, program of study, and profession.

Dr. Sabin has an MS in Computer Science from “Politehnica” University in Bucharest, Romania, and an MS for Teachers in College Teaching and PhD in Computer Science from UNH.

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Renee McCauley College of Charleston

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Renee McCauley is a professor in the omputer Science Department at the College of Charleston in South Carolina, USA, where she directs the master's program in computing and information sciences. She is Chair of the ACM Special Interest Group on Computer

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Amruth N. Kumar Ramapo College of New Jersey

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Amruth Kumar is a Professor of Computer Science. His research interests include Intelligent Tutoring Systems and Computer Science Education Research. He has developed several software tutoring suites for introductory programming including problets (problets.org), epplets (epplets.org), solvelets (solvelets.org) and auglets (auglets.org), funded by the National Science Foundation. He is a Distinguished Member of the ACM, and Senior Member and Distinguished Contributor of IEEE. He has a PhD from the University at Buffalo.

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Abstract

The Computing Curricula 2020 (CC2020) report, issued by the ACM and IEEE Computer Society, identified knowledge, skills, and dispositions as the three main components of competency for undergraduate programs in computer engineering, computer science, cybersecurity, information systems, information technology, and software engineering, as well as data science. As earlier generations of curricular guidelines in computing have described knowledge and skills to some extent, the notion of dispositions is relatively new to computing.

Dispositions are cultivable behaviors, such as adaptability, meticulousness, and self-directedness, that are desirable in the workplace. Multiple employer surveys and interviews confirm that dispositions are as crucial for success in the workplace as the knowledge and skills students develop in their academic programs of study. As such, the CC2020 report describes eleven dispositions that are expected of competent computing graduates. These are distinct and separate from the technical knowledge and disciplinary skills of computing and engineering. Dispositions are also distinct from baseline or cross-disciplinary skills, such as critical thinking, problem-solving, teamwork, and communication. In contrast, dispositions are inherently human characteristics that describe individual qualities and behavioral patterns that lead to professional success. Dispositions are learnable, not necessarily teachable.

This work-in-progress paper motivates dispositions within computing disciplines and presents the background of this approach. It also discusses the use of reflection exercises and vignettes in understanding, promoting, and fostering behavioral patterns that undergraduate computing students identify as related to dispositions they experience in the course. Preliminary data and results from the study are also presented.

MacKellar, B. K., & Kiesler, N., & Raj, R. K., & Sabin, M., & McCauley, R., & Kumar, A. N. (2023, June), Board 363: Promoting the Dispositional Dimension of Competency in Undergraduate Computing Programs Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43018

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