The transition from university into the workplace can be a shock to the system, especially in computing, where technology, tools, and expectations evolve faster than most curricula can keep up. While degrees tend to produce graduates with solid technical knowledge, many still struggle with other aspects required in the workplace, such as collaborative work, managing ambiguity, and adapting to change. Although the context is still technical, these areas are broader than technical skills and often categorised as dispositions and meta-cognitive skills.
Beyond Technical Skills
For years, employers have voiced concern about graduates being “work-ready.” Reports such as the Shadbolt Review (2016) and work from Skills Development Scotland (2018) highlight that while coding and systems knowledge matter, they’re only part of the picture. What really differentiates strong computing professionals is their ability to reflect, adapt, collaborate, and continue learning throughout their careers.
These aren’t new ideas, but they’ve often been sidelined in technical education, dismissed as “soft skills.” The problem is, these so-called soft skills are both hard to teach and hard to assess, while being essential for success.
The Computing Curricula 2020 (CC2020) framework defines dispositions as the “know why” of professional competence, the motivations, attitudes, and behaviours that drive how knowledge and skills are applied. CC2020 identifies eleven key dispositions, including adaptability, professionalism, collaboration, responsibility, and self-direction.
Meta-cognition is the thinking about thinking. It refers to the ability to plan, monitor, and evaluate one’s own learning and problem-solving. In computing education, it underpins self-regulation, debugging, and reflective practice. Students who are aware of how they think and learn can adapt faster, collaborate better, and handle uncertainty with confidence, qualities employers prize (Flavell, 1979; Schraw & Dennison, 1994; Zimmerman, 2002; Villarroel et al., 2018).
Why This Matters for Computing Education
Despite their importance, dispositions and meta-cognitive skills remain under-theorised and under-assessed in computing curricula. Frameworks like CC2020 give us a structure of what to teach, but we still need to understand how to intentionally develop and evaluate these capabilities through authentic learning experiences, reflection, and work-integrated projects.
Within SICSA and beyond, there is growing recognition that developing “work-ready” graduates requires more than content mastery. It demands a shift towards competency-based education, integrating knowledge (“know what”), skills (“know how”), and dispositions (“know why”) within authentic, reflective learning environments (Frezza et al., 2018; Clear et al., 2020).
Towards a More Human-Centred Computing Curriculum
If we want computing graduates to thrive in a world shaped by automation and AI, we must prepare them not just to code, but also to reflect, adapt, and collaborate across disciplines and contexts. Embedding dispositions and meta-cognitive development within computing education is not just about employability; it’s about fostering lifelong learners who can shape the technologies of the future with creativity, integrity, and resilience.
References
CC2020 Task Force (2020) Computing Curricula 2020: Paradigms for Global Computing
Education. New York, NY, USA: ACM. Available at: https://doi.org/10.1145/3467967
Clear, A. et al. (2020) ‘Designing Computer Science Competency Statements: A Process and
Curriculum Model for the 21st Century’, in Proceedings of the Working Group Reports on
Innovation and Technology in Computer Science Education. ITiCSE ’20: Innovation and
Technology in Computer Science Education, Trondheim Norway: ACM, pp. 211–246.
Available at: https://doi.org/10.1145/3437800.3439208
Flavell, J.H. (1979) ‘Metacognition and cognitive monitoring: A new area of cognitive–
developmental inquiry.’, American Psychologist, 34(10), pp. 906–911.
Available at: https://doi.org/10.1037/0003-066X.34.10.906
Frezza, S. et al. (2018) ‘Modelling competencies for computing education beyond 2020: a research based approach to defining competencies in the computing disciplines’, in Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education. ITiCSE ’18: 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education, Larnaca Cyprus: ACM, pp. 148–174. Available at: https://doi.org/10.1145/3293881.3295782