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

   https://doi.org/10.18260/1-2--43018  

   MacKellar, Bonnie; Kiesler, Natalie; Raj, Rajendra; Sabin, Mihaela; McCauley, Renee; Kumar, Amruth (June 2023, ASEE Conferences)

   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. 

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2. Promoting the Dispositional Dimension of Competency in Undergraduate Computing Programs

   https://doi.org/10.18260/1-2--43018  

   MacKellar, Bonnie; Kiesler, Natalie; Raj, Rajendra K; Sabin, Mihaela; McCauley, Renee; Kumar, Amruth (June 2023, 2023 ASEE Annual Conference & Exposition)

   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. 

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3. Fostering Dispositions and Engaging Computing Educators

   https://doi.org/10.1145/3545947.3569592  

   Sabin, Mihaela; Kiesler, Natalie; Kumar, Amruth N.; MacKellar, Bonnie K.; McCauley, Renee; Raj, Rajendra K.; Impagliazzo, John (March 2022, Proceedings of the 54th ACM Technical Symposium on Computer Science Education (SIGCSE 2023))

   Dispositions are cultivable behaviors desirable in the workplace. Examples of dispositions are being adaptable, meticulous, and self-directed. The eleven dispositions described in the CC2020 report should not be confused with the professional knowledge of computing topics, or with skills, including technical skills, along with cross-disciplinary skills such as critical thinking, problem-solving, teamwork, or communication. Dispositions, more inherent to human characteristics, identify personal qualities and behavioral patterns important for successful professional careers. The leaders of this special session collaborate on a multi-institutional project funded by the National Science Foundation. Using their experiences at four higher education institutions, they will demonstrate how to foster dispositions among computing students through two hands-on activities. The audience will get first-hand experience using reflection exercises and vignettes, and will participate in debating their design, merits, and limitations. The resulting interaction will provide the audience ample time to discuss the benefits and challenges of incorporating and fostering dispositions in computing programs. It is hoped that participants will leave with concrete ideas on how to extend the current work to their own courses, programs, and institutions. 

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4. Interpreting the ABET Computer Science Criteria Using Competencies

   https://doi.org/10.1145/3478431.3499293  

   Raj, Rajendra K.; Kumar, Amruth N.; Sabin, Mihaela; Impagliazzo, John (February 2022, 53rd ACM Technical Symposium on Computer Science Education (SIGCSE 2022)

   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. 

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5. Computing Competencies: CC2020 Dispositions versus SFIA Responsibility Characteristics

   Bowers, David S.; Sabin, Mihaela; Raj, Rajendra K.; Impagliazzo, John (March 2022, EDUCON2022 – IEEE Global Engineering Education Conference)

   In the past decade, academic computing curricular guidelines have shifted from specifying knowledge and occasionally technical skills to establishing the overall competence expected of graduates. For instance, Computing Curricula 2020 (CC2020) guidelines identify competency as knowledge, skills, and dispositions where “dispositions” correspond to the behavioral and professional characteristics driven by employer needs and captured by industry-driven frameworks, such as the Skills Framework for the Information Age (SFIA). Computing programs thus must also ensure that graduates have these characteristics to improve initial employment and long-term career prospects. This paper aims to understand and achieve consistency between academia and industry curricular frameworks. The CC2020 dispositions map to the responsibility characteristics for SFIA Level 3, the level appropriate for a new graduate. As the mapping is not one-to-one, the paper reviews the extent to which each SFIA responsibility characteristic requires and enables the CC22020 dispositions, identifying potential shortcomings and, conversely, the importance of each disposition as it supports the responsibility characteristics. The developed mapping is validated by relating the CC2020 dispositions to the SFIA behavioral factors, the principal “21st Century Skills,” and relevant competency-based educational frameworks. Thus, dispositions in competency-focused curricula map to the actual competencies sought by employers. Finally, the paper postulates that future computing curricula must further develop the CC2020 dispositions and relate them to SFIA to guide academic programs in their preparation of career-ready graduates to reduce the current “skills gap”. 

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