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Title: Interpreting the ABET Computer Science Criteria Using Competencies
Since the early 21st century, ABET’s accreditation criteria have focused on learning outcomes (what students learn) rather than what professors teach. Such accreditation criteria bring to bear the need for programs to establish clear learning objectives and assessment processes that ensure that program graduates have the requisite technical and professional preparation. To this end, ABET defines student outcomes as “what students are expected to know and be able to do by the time of graduation,” further noting that these outcomes “relate to the knowledge, skills, and behaviors that students acquire as they progress through the program.” With the recent release of Computing Curricula 2020 (CC2020), the competencies of computing program graduates have received additional attention. CC2020 describes competency as “comprising knowledge, skills, and dispositions that are observable in accomplishing a task within a work context.” ABET’s student outcomes thus largely correspond to the CC2020 competencies of program graduates. This paper is a first attempt to reconcile the two notions in the context of computer science. It presents the relevant background and discusses student competencies and their assessments that focus on competency-based learning in computer science. The contributions of this paper are (1) forging an improved shared understanding of computing competencies and (2) an interpretation of ABET’s student outcomes to improve the competency, including dispositions, expectations of computer science graduates.  more » « less
Award ID(s):
1922169 2110771
PAR ID:
10319439
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
53rd ACM Technical Symposium on Computer Science Education (SIGCSE 2022
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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