Computing Curricula 2001

-- DRAFT (March 6, 2000) --

Chapter 6
Defining a Curriculum

In order to develop a curriculum, it is essential to develop a detailed understanding of the knowledge encompassed by that discipline. As we note in Chapter 4, the CC2001 Task Force has decided that this accounting must be broad enough to accommodate the range of subdisciplines that come under the general rubric of computing. For areas such as information systems and software engineering, our task force can rely on recent reports issued by curriculum committees in those areas [21, 38]. For computer science and computer engineering, the CC2001 Task Force has the central responsibility for developing that updated body of knowledge. To this end, we have identified a set of knowledge areas and appointed knowledge area focus groups to define the body of knowledge for that area. This process is described in more detail in the section entitled "Defining the body of knowledge" below.

Although the definition of the body of knowledge represents a central task of the Computing Curricula 2001 project, it is not sufficient on its own. In some ways, viewing the entire computing curriculum as a body of knowledge misses the forest for the trees. To develop a more complete vision of the curriculum and its implementation, it is important to adopt a more holistic perspective, in which broader issues are allowed to cut across the lines represented by individual knowledge areas. The knowledge areas, after all, reflect the boundaries of established subdisciplines. Using these boundaries as the organizing principle for the curriculum has the conservative structure of reinforcing the existing structure. New curricular ideas and pedagogical strategies often emerge from explorations that transcend those disciplinary boundaries.

To encourage the development of a holistic vision of the curriculum, the CC2001 Task Force established six pedagogy focus groups, with the following areas of concern:

1. Introductory topics and courses
2. Supporting topics and courses
3. The computing core
4. Professional practices
5. Advanced study and undergraduate research
6. Computing across curricula

The charter for each of these groups appears later in this chapter, and the final reports from each group will -- in later drafts -- constitute the next six chapters of the report.

6.1 Defining the body of knowledge

Computing Curricula 1991 organized the undergraduate curriculum by dividing it into nine knowledge areas. Over the last decade, the discipline of computing has grown substantially, to the point that the nine areas identified by Computing Curricula 1991 are no longer sufficient to encompass the knowledge that students are likely to encounter in an undergraduate curriculum. After experimenting with several organizational structures, the CC2001 Task Force has defined an expanded set of 14 knowledge areas, as shown in Figure 6-1:

Figure 6-1. Knowledge areas in Computing Curricula 2001

0. Discrete Structures (DS) 1. Programming Fundamentals (PF) 2. Algorithms and Complexity (AL) 3. Programming Languages (PL) 4. Architecture (AR) 5. Operating Systems (OS) 6. Human-Computer Interaction (HC) 7. Graphics, Visualization, and Multimedia (GR) 8. Intelligent Systems (IS) 9. Information Management (IM) 10. Net-Centric Computing (NC) 11. Software Engineering (SE) 12. Computational Science (CN) 13. Social, Ethical, and Professional Issues (SP)

This revised list of knowledge areas differs from that used in Computing Curricula 1991 in the following ways:

• Discrete Structures (DS) has been added as a separate area. In Computing Curricula 1991, discrete mathematics appears only as a prerequisite for topics that require mathematical maturity. The assumption, presumably, is that such mathematical maturity would come from prior mathematical training or from college-level courses in mathematics. Unfortunately, most mathematics courses in universities -- responding to the needs of the physical sciences and classical engineering fields -- focus on calculus and other aspects of continuous mathematics rather than on the discrete mathematics required for most computing disciplines. As a result, the necessary discrete mathematics is often taught by faculty in computer science or related departments. The CC2001 Task Force has chosen to emphasize the dependency of computing on discrete mathematics by including it as a separate knowledge area.

• The need to include instruction in the use of a programming language has been made explicit by the inclusion of a distinct knowledge area on Programming Fundamentals (PF). Computing Curricula 1991 defined a knowledge area entitled "Introduction to a Programming Language" but identified it as an optional component of the curriculum. In part, introductory programming was left out of the common requirements in the hope that an increasing number of students would acquire the necessary skills and experience in secondary school. Unfortunately, this prediction has not been realized. Despite the overwhelming increase in the availability of computing resources to secondary schools, many students arrive at universities with little understanding of programming discipline and the basic principles of software design. For this reason, the CC2001 Task Force has chosen to define a separate Programming Fundamentals area that enumerates the basic programming skills that all students of computing must acquire to prepare themselves for more advanced study.

• The knowledge area on Social, Ethical, and Professional Issues (SP) has been integrated into the structure of the curriculum in a way that gives it equal weight with the other knowledge areas. Since the publication of Computing Curricula 1991, there has been a growing consensus that all students of computing must be made aware of the social implications of their work and the ethical responsibilities of being a computing professional. This topic has been identified as a "tenth strand" in the computing curriculum, on an equal footing with the nine subject areas identified by Computing Curricula 1991 [27]. The CC2001 Task Force has therefore included social, ethical, and professional issues as part of the body of knowledge.

• Graphics, Visualization, and Multimedia (GR) and Net-Centric Computing (NC) have been added as separate knowledge areas. Many areas of computing have expanded dramatically since the publication of Computing Curricula 1991. As a result, some areas that were formerly topics within a more general area have grown to such an extent that they can no longer fit appropriately into the older structure.

After making a preliminary identification of the knowledge areas in early 1999, the Curriculum 2001 task force appointed a knowledge area focus group to take responsibility for each of the areas. The charge to each knowledge area focus group appears in Figure 6-2. The members of each focus group appear in the acknowledgments in Chapter 14.

Figure 6-2. Charter for the Knowledge Area Focus Groups

Each focus group assigned to a specific focus area will have a chair and preferably a co-chair. The chair and co-chair of each focus area must be experts in the assigned area. Each focus group may invite up to five additional members. Each focus group will: Review and firm up the scope of the focus area drafted by the joint task force members. Finalize the list of individual topics associated with the focus area. Comment on the three processes -- theory, abstraction, and design -- as well as the breadth and depth issues documented in Computing Curricula 1991. Decide the required mathematics and physical sciences. Highlight changes compared to Computing Curricula 1991, if applicable. Separate the topics into two levels, corresponding to core topics required of all students in computing and more advanced electives. Suggest model courses and the corresponding lecture/lab hours, with specific course objectives and expected learning outcome, by indicating which topics are included in each course.

The knowledge area focus groups deliberated over the spring of 1999 and submitted preliminary reports to the CC2001 Task Force. The Computing Curricula 1991 steering committee reviewed these reports at its meeting in June 1999. The review process at that meeting had three goals:

1. To monitor the work of each focus group and make sure that it had fulfilled its charge. If the steering committee could identify omissions in the report, the focus groups were asked to go back and resupply the missing material.

2. To review the set of knowledge units identified with each area and assess whether those knowledge units provide adequate coverage of the area. Once again, if the steering committee found problems in the focus group report, it asked the focus group to provide any necessary updates.

3. To determine which knowledge units in each area would be part of the required core. Because each knowledge area focus group is composed of experts in that area, the individuals are likely to have a strong predisposition to be proponents for that area. As a result, the Curriculum 2001 task force expected each knowledge area group to identify more core topics than could be justified under our minimalist definition of the core. As noted in Chapter 5, the steering committee had agreed that "the core will consist of those topics for which there is a broad consensus that the topic is essential to undergraduate degrees. . . ." If the steering committee itself could not find such a consensus in support of a topic, we eliminated it from the core.

Figure 6-3. Tentative list of topics in the computer science body of knowledge

DS. Discrete Structures    DS1. Functions, relations, and sets    DS2. Basic logic    DS3. Proof techniques    DS4. Basics of counting    DS5. Graphs and trees PF. Programming Fundamentals    PF1. Algorithms and problem-solving    PF2. Fundamental programming constructs    PF3. Basic data structures    PF4. Recursion    PF5. Abstract data types    PF6. Object-oriented programming    PF7. Event-driven and concurrent programming    PF8. Using modern APIs AL. Algorithms and Complexity    AL1. Basic algorithmic analysis    AL2. Algorithmic strategies    AL3. Fundamental computing algorithms    AL4. Distributed algorithms    AL5. Basic computability theory    AL6. The complexity classes P and NP    AL7. Automata theory    AL8. Advanced algorithmic analysis    AL9. Cryptographic algorithms    AL10. Geometric algorithms PL. Programming Languages    PL1. History and overview of programming languages    PL2. Virtual machines    PL3. Introduction to language translation    PL4. Language translation systems    PL5. Type systems    PL6. Models of execution control    PL7. Declaration, modularity, and storage management    PL8. Programming language semantics    PL9. Functional programming paradigms    PL10. Object-oriented programming paradigms    PL11. Language-based constructs for parallelism AR. Architecture    AR1. Digital logic and digital systems    AR2. Machine level representation of data    AR3. Assembly level machine organization    AR4. Memory system organization    AR5. I/O and communication    AR6. CPU implementation OS. Operating Systems    OS1. Operating system principles    OS2. Concurrency    OS3. Scheduling and dispatch    OS4. Virtual memory    OS5. Device management    OS6. Security and protection    OS7. File systems and naming    OS8. Real-time systems HC. Human-Computer Interaction    HC1. Principles of HCI    HC2. Modeling the user    HC3. Interaction    HC4. Window management system design    HC5. Help systems    HC6. Evaluation techniques    HC7. Computer-supported collaborative work

GR. Graphics    GR1. Graphic systems    GR2. Fundamental techniques in graphics    GR3. Basic rendering    GR4. Basic geometric modeling    GR5. Visualization    GR6. Virtual reality    GR7. Computer animation    GR8. Advanced rendering    GR9. Advanced geometric modeling    GR10. Multimedia data technologies    GR11. Compression and decompression    GR12. Multimedia applications and content authoring    GR13. Multimedia servers and filesystems    GR14. Networked and distributed multimedia systems IS. Intelligent Systems    IS1. Fundamental issues in intelligent systems    IS2. Search and optimization methods    IS3. Knowledge representation and reasoning    IS4. Learning    IS5. Agents    IS6. Computer vision    IS7. Natural language processing    IS8. Pattern recognition    IS9. Advanced machine learning    IS10. Robotics    IS11. Knowledge-based systems    IS12. Neural networks    IS13. Genetic algorithms IM. Information Management    IM1. Database systems    IM2. Data modeling and the relational model    IM3. Database query languages    IM4. Relational database design    IM5. Transaction processing    IM6. Distributed databases    IM7. Advanced relational database design    IM8. Physical database design NC. Net-Centric Computing    NC1. Introduction to net-centric computing    NC2. The web as an example of client-server computing    NC3. Building web applications    NC4. Communication and networking    NC5. Distributed object systems    NC6. Collaboration technology and groupware    NC7. Distributed operating systems    NC8. Distributed systems SE. Software Engineering    SE1. Software processes and metrics    SE2. Software requirements and specifications    SE3. Software design and implementation    SE4. Verification and validation    SE5. Software tools and environments    SE6. Software project methodologies CN. Computational Science    CN1. Numerical analysis    CN2. Scientific visualization    CN3. Architecture for scientific computing    CN4. Programming for parallel architectures    CN5. Applications SP. Social, Ethical, and Professional Issues    SP1. History of computing    SP2. Social context of computing    SP3. Methods and tools of analysis    SP4. Professional and ethical responsibilities    SP5. Risks and liabilities of safety-critical systems    SP6. Intellectual property    SP7. Privacy and civil liberties    SP8. Social implications of the Internet    SP9. Computer crime    SP10. Economic issues in computing    SP11. Philosophical foundations of ethics

6.2 Defining the pedagogical framework

As noted in the introduction to this chapter, defining a body of knowledge for a discipline is not the same as defining a curriculum. While the work of the knowledge area groups in defining the topics that are important within the undergraduate curriculum, it is also important to take a holistic look at the curriculum that transcends the traditional disciplinary boundaries. The CC2001 Task Force established six pedagogy focus groups with the following charges:

1. Introductory topics and courses
   • Identify the goals of the introductory curriculum, typically corresponding to the first year of study
   • Report on both the strengths and weaknesses of the traditional programming-first approach at reaching these goals
   • Provide a short list (ideally consisting of between two and four well-specified options) of alternative approaches

2. Supporting topics and courses
   • Specify goals of courses that support undergraduate computing curricula
   • Identify a minimal list of supporting courses deemed essential to an undergraduate program, as well as additional supporting courses

3. The computing core
   • Specify material that is deemed essential to a foundation in computing
   • Develop the core as a curricular alternative to the traditional approach of organizing programs around artifacts (e.g., courses in compilers, operating systems, databases, and so forth)

4. Professional practices
   • Report on effective education in various aspects of professional practices and on how these needs can be integrated into other courses in the curriculum.

5. Advanced study and undergraduate research
   • Report on coursework beyond the core
   • Include a specification of how many courses (as a minimum) should be included to produce a reasonable undergraduate experience
   • Report on undergraduate research, including an evaluation of various existing models

6. Computing across curricula
   • Articulate those aspects of the computing discipline relevant to all citizens and academic disciplines and propose guidelines for the role computer science can play in helping students achieve that knowledge.

The pedagogy focus groups were formed later in the review process than the counterpart focus groups examining the knowledge areas. The work of the pedagogy focus groups, moreover, is often dependent on the results of the knowledge area focus groups to define the scope of knowledge. The pedagogy focus groups have therefore had a shorter time in which to work.

Despite the limited time, most of the pedagogy focus groups produced draft reports during the second half of 1999. These reports outline the overall direction for each group and serve as a foundation for work over the coming year. These reports, however, were drafted prior to the January 2000 decision by the CC2001 Task Force to expand its scope beyond computer science and computer engineering. The broadening of the definition of the discipline has a substantial effect on the work of many of the pedagogy groups, and the CC2001 Task Force needs to go back to those groups and ask them to review their preliminary reports in light of that change.

In light of the recent change in direction, we have chosen not to include the draft reports from the pedagogy focus groups in this version of the report. They will instead be included in the next release, after the groups have had time to integrate the change in scope.

CC2001 Report DRAFT -- March 6, 2000 This report is a working draft and does not carry any endorsement from the sponsoring organizations