Search for: All records

There can be many conflicting goals for the design of a computer science curriculum including: immediate employability in industry, preparation for long-term success in an ever-changing discipline and preparation for graduate (that is, post-graduate) study. Emphasis on immediate employability may lead to prioritizing current tools and techniques at the expense of foundational and theoretical skills as well as broader liberal-arts education that are crucial to long-term career success and for graduate study. The implications of these conflicting goals include allocation of finite resources (time, courses in the curriculum), unwillingness of students to invest in the mathematics that they see as irrelevant to their immediate career goals, and reluctance of faculty to have their courses driven by a continually evolving marketplace of tools and APIs. A balanced curriculum benefits all stakeholders: students, employers, and faculty. Would a data-driven approach help faculty design curricula that effectively balance these multiple goals? For example, if we ask graduates of computer science programs to reflect on the impact of their undergraduate education, explicitly focusing on short and long-term impact, will there be enough meaningful data to significantly inform curricular design? A recent survey of industry professionals undertaken by the ACM/IEEE-CS/AAAI 2023 Computer Science Curricular Task Force (CS2023) points the way. This column presents one aspect of that survey—a focus on comparing short-term versus long-term views—and calls for similar surveys of industry professionals to be conducted on an ongoing basis to refine our understanding of the role played by various elements of undergraduate computer science curricula in the success of graduates. 

Undergraduate Computer Science (CS) curricular guidelines have been published regularly since 1968, and the latest released in 2013. From early 2021, a task force of the ACM, IEEE-Computer Society, and the Association for the Advancement of Artificial Intelligence (AAAI) has worked on a decennial revision titled the ACM/IEEE-CS/AAAI Computer Science 2023 Curricula (CS2023). The CS2023 task force includes a 17-member steering committee, 17 knowledge area subcommittees, and an international group of disciplinary experts. CS2023 provides curricular content – a knowledge model largely backward compatible with CS2013, supplemented by a competency model – and curricular practices, comprising articles by independent experts on program design and delivery that complement curricular content guidelines. CS2023 will inform educators and administrators on the what, why, and how to cover undergraduate CS over the next decade. Ongoing work on CS2023 has been disseminated widely over the past two years: via the task force website; presentations at computing education conferences, e.g., SIGCSE Technical Symposium 2023; articles, e.g., ACM Inroads; emails to various computing education mailing lists; gathering community feedback via surveys and special sessions; and soliciting and receiving expert blind peer reviews. Building on earlier drafts, a gamma draft was released in September 2023, with the final version due by the end of 2023. This panel examines CS2023 from different perspectives. All panelists serve on the CS2023 steering committee and have an intimate understanding of CS2023. The moderator will lay out its overall vision and structure while panelists will emphasize three major perspectives of CS education: software development fundamentals; systems development; and the increased role of societal, ethical, and professional aspects crucial to a modern CS graduate. Strong interdependencies exist between these perspectives, along with tensions arising from how much can be squeezed into a tight undergraduate CS curriculum. Attendees will take home an understanding of the approach taken by the CS2023 task force, the constraints on curriculum design, and how best to use the CS2023 guidelines to educate the next generation of CS graduates.