Computer science education is in crisis. Our curriculum is dated, our teaching methods and faculty development strategies are inadequate, and the computer science education community is fragmented into interest groups whose interactions are dysfunctional. (Otherwise, we're in pretty good shape!)

Dated Curriculum

Furthermore (and this is quite surprising), the programming methodology that introduces our curricula to thousands of students each year is dominated by a narrow collection of outdated languages and methodologies (procedural programming, top-down decomposition, solving small problems from scratch, absence of teaming, ignorance of formal methods, etc.). Current programming methodologies (event-driven object-oriented design, solving parts of large problems, thinking about complexity from the start, role-playing in teams, use of modern tools for testing and quality assurance, etc.) would be far more effective at preparing students to understand the modern principles of computer science and engineering. Yet these methodologies are not typically introduced until very late in the undergraduate major, if at all.

The subject matter which is absent from our core curricula, due in part to our uncommon obsession with programming, reflects a collective inattention to certain central themes that have emerged in our discipline in the late 1980s and early 1990s. Here are some specific examples:

• The algorithms course usually fails to integrate fundamental concepts of parallelism, especially in its laboratory component. Yet most significant future scientific challenges admit the need for sophisticated algorithms running on parallel and distributed architectures (cf "Computing the Future" and the "grand challenges" of computational science). In fact, I have recently heard textbook authors and educators whimsically refer to the algorithms course as "the CS7 course" as if there have been no fundamental changes in that course since its identification in Curriculum 78!
• The core curriculum has no commitment to subject matter that covers computer networks, theory or practice, in a responsible way. Yet the network has arguably become one of the two or three central topics in the discipline of computing in the last five years. On the other hand, relatively dated and uninteresting subject matter, like compilers and assembly language programming, continue to occupy immovable positions in our core curricula.
• Our curricula rarely provide students with an active appreciation of the paradigm of science, which includes modeling, empiricism, experimentation, measurement of outcomes, and hypothesis testing. There are some very distinguished exceptions, but on the whole the scientific method has failed to become a central component of our curricula, as it should.
• Human-computer interaction, social and professional issues, and organizational aspects of computing, have (at best) marginal presence in our curricula. More often our courses for nonmajors provide students with an appreciation of these important dimensions of our discipline, while our majors are left alone in the lab to master the art of hacking. Majors learn few other concepts that would have important impact on their world view or technical preparedness, such as a commitment to the principles of human-computer interaction in software design projects.
• We have failed to effectively integrate the theory of computation into our core curricula. Many undergraduates are able to put off the "theory" course, and even the discrete math course, until so late in their programs that such courses have little impact on their understanding of the discipline. Many programs have simply given up and dropped the theory of computation course from the major requirements.
• Yesterday's "advanced" topics are today's core topics. Yet, due perhaps to inertia, most programs have not effectively migrated these topics into the core in a timely way.

Teaching and Faculty Development Methodologies

• The large lecture class is still the dominant model for teaching, amidst a preponderance of evidence that students do their best learning in individual and small group settings.
• Textbooks as a medium are often unhelpful, overpriced, and unattractive to students (and faculty), who increasingly prefer alternative styles of teaching and learning. Discovery learning, for example, is effective in a wide range of subject areas.
• Labs above the introductory level are usually unstructured, and lab assignments and methods are too often haphazardly designed and executed. We need to rethink the computer science laboratory experience, especially at the intermediate and advanced levels of the curriculum. Graduates need to be prepared to enter the work force prepared to work effectively in design and programming groups, use modern tools of analysis and synthesis, and communicate effectively with peers and customers on the technical and organizational impact of their work. We are not doing that now, and most of us don't even know how.
• Most teaching methods and learning materials are strongly biased toward a male, individual, isolated work ethic. Lectures, texts and lab assignments favor the learning styles that are dominant within this narrow group. While this is surely not intentional, we need to become more aware and responsive to this problem, so that our discipline appears both accessible and welcoming in the eyes of students who represent the widest range of backgrounds and learning styles.

Community and Infrastructure

This is a loose confederation, at best. Channels of communication seem not to exist at points where they ought to. For instance, it is not clear that there are criteria for membership on the ACM Education Board that would ensure representation from the AP Curriculum Committee, the two-year college programs, the graduate programs, the undergraduate programs, or the various professional education programs that are sponsored by industry.

Moreover, it is not clear that SIGCSE encourages participation by a wide constituency at its annual conference in the spring. What are the criteria for serving on the Program Committee for this very important conference. Where is the representation from top-10 universities with strong undergraduate programs? Where is the AP representative? And so on.

Overall, the computer science education infrastructure seems to be ill-equipped to address the many concerns expressed above, without first becoming functional itself. A first step would be to greatly widen the channels of communication and sense of inclusion among the various groups that represent different levels and interests in the future of computer science education. Much work needs to be done, but we first need to be organized.