Computing Competencies: Mapping CC2020 Dispositions to SFIA Responsibility Characteristics
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”.
2022 IEEE Global Engineering Education Conference (EDUCON)
Digital Object Identifier (DOI)
Bowers, D. S., Sabin, M., Raj, R. K., & Impagliazzo, J. (2022). Computing competencies: Mapping CC2020 dispositions to SFIA responsibility characteristics. 2022 IEEE Global Engineering Education Conference (EDUCON), 428–437. https://doi.org/10.1109/EDUCON52537.2022.9766565