Many factors influence computing graduate employment prospects, including human capital, social capital, individual attributes, individual career-building behaviours, perceived employability, and labour market factors. Whilst most computing graduates go on to be beneficially employed, a small minority remain under-employed or unemployed. Computing curricular recommendations increasingly advocate a competency-based approach to bolster graduates' perceived employability. Hence, the discipline is evolving to incorporate competency-based approaches. However, competency-based can mean any of three different types of competency: technical, personal and professional. Technical Competency is the ability to apply acquired content knowledge and skills to develop solutions to unseen problems. Personal Competency is the personal behaviours and interpersonal skills required for success in the modern workplace. Professional Competency is Technical and Personal combined and applied in a real-world context.

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”.

This Innovative Practice Full Paper addresses the assessment of dispositions which, along with knowledge and skills, form the three legs of competency needed to perform a task in context, as described in recent computing curricular reports, particularly ACM/IEEE Computing Curricula 2020 (CC2020). Here, dispositions in CC2020 express the behavioral characteristics of competence, such as being adaptable, collaborative, or inventive. Instructors have assessed knowledge from the start of computing programs and have paid increased attention to assessing skills in recent decades. However, dispositions and their role within competency is relatively new, with little guidance available for assessing dispositions. Lately, computing instructors have begun to understand the importance of evaluating dispositions during the performance of tasks in the real world or in the context of the industry-based global Skills Framework for the Information Age (SFIA). Hence, this paper develops a criterion-based approach for use by educators in assessing competence based on a reflective portfolio of "real-world" achievements. Building on concepts developed by the UK Institute of Coding and other recent reports, this work demonstrates how this assessment approach relates to industry-based competency frameworks such as SFIA and the European e-Competence Framework (eCF). The paper also explores using the criterion-based approach in a classroom environment to help students focus on particular dispositions. Its main contribution is to advance the competency focus in academic computing programs and future computing curricula.

Professional accreditation in medicine and religious organizations started in the 1800s; business and engineering followed in the early 1900s. Program accreditation in computing commenced in the 1980s after computer science, informatics, and information systems programs had become widespread. In 2008, accrediting bodies in eight countries signed the Seoul Accord to set up mutual recognition of professional computing degrees. Although competency-based learning has existed for centuries, it has only made headway in computing in the last dozen years. Computing Curricula 2020 defined competency as the amalgamation of knowledge, skills, and dispositions. This working group report examines professional accreditation in computing, exploring aspects of professional accreditation criteria that support competency-based learning. The report will help educators understand professional accreditation and competency-based learning worldwide. Finally, it will also guide future efforts contributing to competency-based accreditation.

There exists a significant gap between the requirements specified within higher education qualifications and the requirements sought by employers. The former, commonly expressed in terms of learning outcomes, provide a measure of capability, of what skills have been learnt (an input measure); the latter, commonly expressed in terms of role descriptions, provide a measure of competency, of what a learner has become skilful in (an output measure). Accreditation traditionally provides a way of translating and embedding industry-relevant content into education programmes but current approaches make fully addressing this requirements gap, referred to here as the Capability-Competency Chasm, very difficult. This paper explores current efforts to address this global challenge, primarily through STEM examples that apply within the United Kingdom and European Union, before proposing a way of bridging this chasm through the use of a 21stCentury (C21) skills taxonomy. The concept of C21 Skills Hours as a new input measurement for learning within qualifications is introduced, and an illustrative example is presented to show the C21 skills taxonomy in action. The paper concludes with a discussion of how such a taxonomy can also be used to support a microcredentialing framework that aligns to existing competency frameworks, enabling formal, non-formal and informal learning to all be recognized. A C21 Skills taxonomy can therefore be used to bridge the gap between capability (input) and competency (output), providing a common language both for learning and demonstrating a skill. This approach has profound implications for addressing current and future skills gaps as well as for supporting a transition to more personalised learning within schools, colleges and universities and more lifelong learning both during and outside of employment.

Competency-based learning has been a successful pedagogical approach for centuries, but only recently has it gained traction within computing education. Building on recent developments in the field, this working group will explore competency-based learning from practical considerations and show how it benefits computing. In particular, the group will identify existing computing competencies and provide a pathway to generate competencies usable in the field. The working group will also investigate appropriate assessment approaches, provide guidelines for evaluating student attainment, and show how accrediting agencies can use these techniques to assess the level of competence reflected in their standards and criteria. Recommendations from the working group report are intended to help practical computing education writ large.

The problem is addressed of data which are not only incomplete, but also aggregate in nature. Some difficulties associated with maintaining the consistency of such data are illustrated. These problems arise in particular when it is required that both aggregate and simple data values should be stored. An architecture is proposed for a database management system to handle this class of data, which is termed aggregate-incomplete. A generalized materialization strategy is defined on the basis of the proposed architecture, and it is shown that the consistency problems are reduced to manageable proportions.