Chapter9
Computing Curricula 2001
Computer Science Volume
Chapter 9
Completing the Curriculum
The primary purpose of Chapters 7 and 8 is to outline a variety of approaches for covering the core units in the body of knowledge. As we have emphasized on several occasions in this report, the computer science core does not in itself constitute a complete curriculum. To complete the curriculum, computer science programs must also ensure that students have the background knowledge and skills they need to succeed as well as the chance to do advanced work that goes beyond the boundaries of the core. This chapter offers strategies and guidelines in each of these areas. Section 9.1 describes a set of general requirements that support the broad education of computer science students. Section 9.2 outlines a set of advanced courses to provide depth in the curriculum, which is followed by a discussion of project courses in section 9.3. Finally, section 9.4 provides an overview of a few curricular models that address these goals for a variety of institutions.
9.1 General requirements
A successful computer science graduate needs many skills beyond the technical ones found in the CS body of knowledge. For example, computer science students must have a certain level of mathematical sophistication, familiarity with the methods of science, a sense of how computing is applied in practice, effective communication skills, and the ability to work productively in teams. This chapter outlines several general recommendations for computer science programs seeking to meet these goals.
9.1.1 Mathematical rigor
Mathematics techniques and formal mathematical reasoning are integral to most areas of computer science. The Computing Curricula 1991 report identified theory as one of the three primary foundations of computer science, and we believe strongly that the same principle holds true today. Computer science depends on mathematics for many of its fundamental definitions, axioms, theorems, and proof techniques. In addition, mathematics provides a language for working with ideas relevant to computer science, specific tools for analysis and verification, and a theoretical framework for understanding important computing ideas. For example, functional programming and problem solving draw directly upon the mathematical concepts and notations for functions; algorithmic analysis depends heavily on the mathematical topics of counting, permutations and combinations, and probability; discussions of concurrency and deadlock draw heavily from graph theory; and both program verification and computability build upon formal logic and deduction. Thus, it is critical for computer science programs to include enough mathematics so that students understand the theoretical underpinnings of the discipline.
Given the pervasive role of mathematics within computer science, the CS curriculum must include mathematical concepts early and often. Basic mathematical concepts should be introduced early within a student's course work, and later courses should use these concepts regularly. While different colleges and universities will need to adjust their prerequisite structure to reflect local needs and opportunities, it is important for upper-level computer science courses to make use of the mathematical content developed in earlier courses. This dependency, moreover, should be reflected in the formal prerequisite structure.
In developing these recommendations, the CC2001 Task Force has concluded that computer science programs must take responsibility for ensuring that students get the mathematics they need, especially in terms of discrete mathematics. To this end, the CC2001 report defines a new knowledge area consisting of the discrete mathematics required for an undergraduate program. That area -- Discrete Structures (DS) -- specifies the units and topics that we believe are essential to every undergraduate program. The material on discrete structures can be presented in separate courses or integrated more directly into the curriculum by presenting the mathematical material together with the computer science topics that depend on it. In either case, it is essential to make sure that the curriculum emphasizes the use of discrete mathematical techniques throughout the undergraduate program.
The CC2001 Task Force makes the following recommendations with respect to the mathematical content of the computer science curriculum:
- Discrete mathematics. All students need exposure to the tools of discrete mathematics. When possible, it is best for students to take more than one course in this area, but all programs should include enough exposure to this area to cover the core topics in the DS area. Strategies for integrating discrete mathematics into the introductory curriculum are discussed in section 7.4.
- Additional mathematics. Students should take additional mathematics to develop their sophistication in this area. That mathematics might consist of courses in any number of areas including statistics, calculus, linear algebra, numerical methods, number theory, geometry, or symbolic logic. The choice should depend on program objectives, institutional requirements, and the needs of the individual student.
9.1.2 The scientific method
As noted in Computing Curricula 1991, the process of abstraction (data collection, hypothesis formation and testing, experimentation, analysis) represents a vital component of logical thought within the field of computer science. The scientific method represents a basis methodology for much of the discipline of computer science, and students should have a solid exposure to this methodology.
To develop a firm understanding of the scientific method, students must have direct hands-on experience with hypothesis formulation, experimental design, hypothesis testing, and data analysis. While a curriculum may provide this experience in various ways, it is vital that students must "do science" -- not just "read about science."
The CC2001 Task Force therefore makes the following recommendations about science:
- Students must develop an understanding of the scientific method and experience this mode of inquiry in courses that provide some exposure to laboratory work.
- Students may acquire their scientific perspective in a variety of domains, depending on program objectives and their area of interest.
9.1.3 Familiarity with applications
With the broad range of applications of computing in today's society, computer scientists must be able to work effectively with people from other disciplines. To this end, the CC2001 Task Force recommends that all computer science students should:
- Engage in an in-depth study of some subject that uses computing in a substantive way.
Computing students have a wide range of interests and professional goals. For many students, study of computing together with an application area will be extremely useful. Such work might be accomplished in several ways. One approach is to integrate case studies into computer science courses in a way that emphasizes the importance of understanding the application domain. Other approaches might include an extended internship experience or the equivalent of a full semester's work that would count toward a major in that discipline. Such opportunities certainly exist in such fields as psychology, sociology, economics, biology, business, or any of the science or engineering disciplines. With some creativity, it is also possible to find applications to areas that might be considered farther afield, often through innovative approaches beyond the scope of a standard computer science curriculum.
9.1.4 Communications skills
A widely-heard theme among employers is that computer scientists must be able to communicate effectively with colleagues and clients. Because of the importance of good communication skills in nearly all computing careers, computer science students must sharpen their oral and writing skills in a variety of contexts -- both inside and outside of computer science courses. In particular, students in computer science programs should be able to:
- Communicate ideas effectively in written form
- Make effective oral presentations, both formally and informally
- Understand and offer constructive critiques of the presentations of others
While institutions may adopt different strategies to accomplish these goals, the program of each computer science student must include numerous occasions for improving writing and practicing oral communication in a way that emphasizes both speaking and active listening skills.
At a minimum, a computer science curriculum should require:
- Course work that emphasizes the mechanics and process of writing
- At least one formal oral presentation to a group
- The opportunity to critique at least one oral presentation
Furthermore, the computer science curriculum should integrate writing and verbal discussion consistently in substantive ways ways. Communication skills should not be seen as separate but should instead be fully incorporated into the computer science curriculum and its requirements.
9.1.5 Working in teams
Few computer professionals can expect to work in isolation for very much of the time. Software projects are usually implemented by groups of people working together as a team. Computer science students therefore need to learn about the mechanics and dynamics of effective team participation as part of their undergraduate education. Moreover, because the value of working in teams (as well as the difficulties that arise) does not become evident in small-scale projects, students need to engage in team-oriented projects that extend over a reasonably long period of time, possibly a full semester or a significant fraction thereof.
To ensure that students have the opportunity to acquire these skills as undergraduates, the CC2001 Task Force recommends that all computer science programs include the following:
- Opportunities to work in teams beginning relatively early in the curriculum.
- A significant project that involves a complex implementation task in which both the design and implementation are undertaken by a small student team. This project is often scheduled for the last year of undergraduate study, where it can serve as a capstone for the undergraduate experience. Strategies for structuring this project experience are discussed in section 9.3 later in this chapter.
The experience that students derive from a significant team project can be enhanced further by using teams that cross disciplinary boundaries. As an example, computer science students can be paired with students in biology to conduct a project in the emerging area of biocomputation. Such a project will require expertise from both disciplines, along with strategies to support effective communication across the disciplinary boundary. The ABET 2000 report [ABET2000] specifically endorses the concept of interdisciplinary team projects, and the CC2001 Task Force agrees that such projects can provide a rich and valuable experience for students, both inside and outside of computer science.
9.1.6 The complementary curriculum
Particularly in times of intense demand for computer science graduates, institutions feel pressured to ensure that graduates have specific skills to meet the needs of employers. On the one hand, the goal of producing graduates with the skills necessary for employment is certainly a positive one. On the other hand, it is important to keep in mind that students are best served not by mastering specific skills that may soon be obsolete, but instead by gaining an enduring understanding of theory and practice that will allow them to maintain their currency over the long term. The best way to think about this aspect of student preparation is that both employers and the students themselves should see computer science graduates as agents of change capable of moving into employment with skills and expectations that prove of enduring value to those organizations.
To empower students in this way, the curriculum must encourage them to develop a set of transferable skills that enhance their overall efficacy. To some extent, these skills include those listed in the preceding sections. But they also include skills that are not typically developed through coursework, such as the ability to write an effective résumé, manage time effectively, conduct library research, maintain professional responsibility, remain up to date, engage in life-long learning, and so on. This constellation of skills has been identified as the complementary curriculum.
One way to ensure that students develop these skills is to weave them into the fabric of the traditional curriculum. There is, however, always a danger that elements of the complementary curriculum absorb so much time that they overwhelm the technical material. There are delicate issues of balance here, and curriculum and course designers must find the proper mix.
9.2 Advanced courses
We use the term advanced course to mean courses whose content is substantially beyond the material of the core. The units in the body of knowledge give testimony to the rich set of possibilities that exist for such courses, but few if any institutions will be able to offer courses covering every unit in detail. Institutions will wish to orient such courses to their own areas of expertise, guided by the needs of students, the expertise of faculty members, and the needs of the wider community.
The CC2001 Task Force has benefited from the work of one of its pedagogy focus groups, which produced a set of advanced courses using the framework provided by the body of knowledge. A set of potential course titles for each knowledge area appears in Figure 9-1. We have, however, decided not to include in the printed report full descriptions of the advanced courses unless those courses are part of one of the curricular tracks described in Chapter 8. Instead, we plan to create web pages for these courses, which will be accessible from the CC2001 web page. By doing so, we will reduce the size of the printed document and, at the same time, allow the documentation associated with each advanced course to remain more up to date.
Figure 9-1. Advanced courses by area
9.3 Project courses
As discussed in section 9.1.5, the CC2001 Task Force believes it is essential for all undergraduates to complete a significant team project that encompasses both design and implementation. Depending on the structure of the institution, there are several workable strategies for providing this type of practical experience. In some cases, it may be possible to work with local companies to create internships in which students have the opportunity to engage in projects in an industry setting. More often, however, computer science departments will need to offer this type of project experience through the curricular structure.
The course descriptions in Appendix B offer several models for including project work in the curriculum. The first strategy is simply to include a project component as part of the required intermediate or advanced course that covers the core material on software engineering. This strategy is illustrated by the course
which includes a team project along with a significant amount of additional material. As long as students have sufficient time to undertake the design and implementation of a significant project, this approach is workable. The projects in such courses, however, tend to be relatively small in scale, simply because the time taken up by the software engineering material cuts into the time available for the project.As an alternative, the CC2001 Task Force recommends that curricula include a capstone project that allows students to bring together all the skills and concepts that they have previously learned during their undergraduate courses. Such a course might include a small amount of additional material, but the major focus must be on the project. Appendix B includes both
which provides a one-semester capstone and the two-semester sequence The two-semester version offers students much more time to complete a large project, but may not be feasible given the time constraints of the undergraduate program in the United States.9.4 Sample curricula
One of the great difficulties in designing curriculum guidelines is the enormous variation that exists between programs at different types of universities and colleges. Given the range of expectations for degree programs -- particularly internationally but also within the United States -- it is impossible to come up with a single model that fits all institutions. Chapters 7 and 8 offer several different approaches for the introductory and intermediate levels of the curriculum that can presumably be adapted to many different institutions. The purpose of this section is to illustrate how the complete curriculum could be embedded into degree programs at a range of institutional types.
Perhaps the most significant variable among academic programs is the number of computer science courses required for an undergraduate degree. In institutions outside the United States, university students typically focus on a single subject, with perhaps a few additional courses in closely related fields. Under this type of educational system, a student might take 3-4 computer science courses in the first year, 4-5 in the second, and 5-6 in each of the third and fourth years. An undergraduate at such an institution would therefore complete 17-21 computer science courses in a four-year degree. In the United States, this level of concentration is extremely rare. At universities, for example, students typically take 12-15 computer science courses as undergraduates, filling out their programs with general education requirements and electives. Students at liberal-arts colleges take 9-12 computer science courses, rounding out their education with a strong liberal-arts experience and often a second major or minor in another field of study. Thus, the number of computer science courses that constitute an undergraduate degree can vary by as much as a factor of two.
It is important to realize that a smaller curriculum does not mean a weaker curriculum. Any curriculum that follows the guidelines proposed in this report must provide a rigorous grounding in the fundamentals of computer science. Regardless of the characteristics and expectations of the educational institution, every curriculum must
- Cover all 280 hours of core material in the CS body of knowledge
- Require sufficient advanced coursework to provide depth in at least one area of computer science
- Include an appropriate level of supporting mathematics
- Offer students exposure to "real world" professional skills such as research experience, teamwork, technical writing, and project development
The next three sections describe curricular models designed to fit the needs of the following broad classes of institution:
- A research-oriented university in the United States
- A university in which undergraduate education is focused on a single discipline, as is typically the case in countries outside North America
- An institution, such as a liberal-arts college in the United States, with a small computer science department
9.4.1 Curriculum model for a research university in the United States
The purpose of this model is to show the correspondence between CC2001 and what is typically done in undergraduate programs in U.S. research universities. These programs typically have a fairly large faculty capable of providing considerable depth and breadth in computer science. It is often an implicit goal that all students will have sufficient depth for both graduate study and work in industry. For many of these schools, another goal is for their students to have a smooth path between taking the first two years of the degree at a two-year institution, such as a community college in the United States, and the rest of the degree at the university.In designing a university curriculum, any combination of an introductory track described in Chapter 7 with either the traditional, systems, or web-based intermediate curriculum from Chapter 8 can be made to work. The most common choices of introductory sequences in such settings are the two- and three-course versions of the imperative and objects-first introductions, described in sections 7.6.1 and 7.6.2, respectively. It is important to note, however, that these implementations are not simply an instantiation of current practice. Each of these sequences puts a significant amount of modern material in such areas as networking and databases into the required introductory and intermediate courses. In many research universities today, that material is found only in advanced elective courses, which may therefore be missing from some student programs.
Figure 9-2 outlines the structure of a curriculum designed for a U.S. research university. The sections that follow offer additional notes on the design decisions that affect the overall structure of the model.
Figure 9-2. University model (US)
|
Introductory and intermediate courses As noted in the preceding section, any of the introductory sequences followed by anything other than the highly compressed model is appropriate for the research university setting. The curriculum outlined in Figure 9-2, for example, uses a three-course imperative introductory sequence and the traditional approach to the intermediate level, with the following modifications:
- We have added the optional course CS120(Introduction to Computer Organization), as outlined in the discussion of the systems-based approach.
- We have replaced the pair of "traditional" courses in artificial intelligence and databases, CS260 and CS270, with the combined course CS262 (Information and Knowledge Management), as outlined in the discussion of the compressed approach.
One of the great strengths of the CC2001 core is the requirement of material in information management and intelligent systems. Many schools have put almost all such material into elective courses. For this curriculum, we suggest one required course combining the two, with the expectation that many schools would additionally continue to run advanced electives in both. Science and mathematics A deep grounding in science and mathematics is one of the usual goals of research university computer science programs. We therefore require two semesters of science. In keeping with the desire for mathematical depth and maturity, we require the following courses in mathematics:
- One semester of discrete structures, represented by Discrete Structures for Computer Science. Institutions that wish to offer a more thorough grounding in this material could easily expand this coverage by implementing the two-semester sequence Discrete Structures I-Discrete Structures II.
- An introduction to calculus at the level necessary to take advanced math electives such as logic, linear algebra, and abstract algebra. Depending on the institution, the calculus requirement might range from a one-semester course to a sequence with three or more courses. On the whole, we believe that it is often more appropriate for computer science students to take less calculus and more courses in discrete mathematics or other material more directly relevant to the practice of computer science. In many institutions, however, the structure of the mathematics curriculum may be outside the control of the computer science program, leaving relatively little flexibility for the department.
- One semester of probability and statistics.
- At least one additional semester of advanced mathematics taken as an elective.
In addition to the advanced material, a undergraduate program must also expose students to the issues involved in programming large-scale systems. Implementing such a requirement allows for wide variations in strategy. Students might gain their experience with programming in the large through either a one-semester capstone project (CS490), a two-semester capstone project (CS491-CS492), or an advanced software development course (CS390).
For undergraduates, one of the great strengths of a research university is that the faculty are actively engaged in the process of extending the frontiers of the discipline. For many students, however, that aspect of the academic mission is largely invisible, because relatively few have the opportunity to participate in research projects during their undergraduate years. Students who have the chance to participate gain significantly from that experience in the following ways:
- They get to experience firsthand the excitement associated with creative research.
- They develop a strong connection to a faculty member who can serve as a mentor.
- They establish a track record of project experience that will prove useful to them, both in industry and in securing admission to graduate programs.
9.4.2 A discipline-based model
In the United States and Canada, students at a university generally take a large fraction of their course work outside their area of specialization. In other countries, this generalist approach to university education is rare. Instead, students are expected to concentrate on a single field of study, possibly augmented by a few courses in closely related disciplines. We refer to such curricula as discipline based. The discipline-based approach is typical of computer science curricula in England, for example, where such programs have a three-year duration. Other countries often use a four-year model, but it is relatively easy to tailor the basic discipline-based model to fit local conditions.Discipline-based curricula typically offer some level of flexibility at all levels of the program. In the first year, for example, the flexibility comes from the opportunity students have to widen their perspective through the choice of electives. Those electives may address some interesting application area, for example, and so enhance or broaden the student's overall education. Those electives may also be used to provide opportunities for exploration if the student is unsure of the intended nature of the final degree. The precise details here will vary from institution to institution and depend on matters such as the entry qualifications for the specific program of study. For instance, some institutions may require that applicants already hold a relatively advanced qualification in mathematics, or even in computer science itself. Then the details of the program need to be adjusted to reflect such considerations.
Another opportunity for flexibility occurs in the final year where optional advanced classes allow a student to specialize, often with a view to exploring or enhancing career prospects in a particular direction. By this stage it is expected that courses are leading students to the frontiers of their subject, at least when viewed from the perspective on an undergraduate education.
A three-year implementation of a discipline-based curriculum appears in Figure 9-3. This curriculum reflects the following design decisions beyond the general guidelines proposed in this report:
- Programming is difficult to teach and requires considerable time and attention in the curriculum. The courses that provide students with a foundation in programming are critical to the curriculum. Students must have frequent and repeated opportunities to practice their programming skills throughout their degree program in a way that allows later courses to build on the work of earlier ones.
- The overall program must include extensive opportunities for students to develop practical skills. Most courses in a computer science program must include a laboratory component that requires students to develop their technical skills and acquire an understanding of effective professional practice. Students must not be allowed to pass a course without demonstrating an appropriate level of mastery of the associated practice.
- The sample curriculum does not include a specific course in science but instead assumes that this material can be integrated into the elective structure. The experimental method can be addressed in the context of a course on Human Computer Interaction, for example; teaching such material in the setting of computer science is far preferable to teaching it in isolation.
- Insofar as possible, it is important to teach supporting material in the context of its application to computer science. The comment in the previous point about teaching material in context applies broadly in the curriculum. Much of the supporting material -- including mathematics, certain transferable skills, professional practice, and so on -- can be taught more effectively in context.
Figure 9-3. Discipline-based model
|
9.4.3 A small department model
This curriculum model is designed for computer science programs in small departments. We use the term "small department" in an informal way, since what is considered "small" at one school may be thought of as "rather large" at another. In general, the following model would be appropriate for departments with fewer than five or six faculty, but may nonetheless be attractive to larger departments as well.The primary effect of a small faculty on the design of the curriculum is that the number of computer science courses in the program will be less than that typically found at larger schools. For example, the university model for U.S. universities described in section 9.4.1 contains 15 computer science courses; the discipline-based model from section 9.4.2 contains 21. Offering this many courses would not be possible in a department with five or six faculty members. A major in a small department might typically include 9-11 computer science courses, along with supporting mathematics classes and a project.
The small-department model is illustrated in Figure 9-4, which specifies a total of 14 courses, organized into the following groups:
| 1. | Supporting mathematics courses | 3 |
| 2. | Introductory computer science courses | 2 |
| 3. | Intermediate computer science courses | 5 |
| 4. | Advanced computer science electives | 3 |
| 5. | Capstone project | 1 |
| Total courses | 14 |
Figure 9-4. Small department model
|
The courses in each of these groupings are described in more detail in the sections that follow. Supporting mathematics courses The number of supporting mathematics courses often depends on how much space is available in the curriculum. While four or five supporting courses is certainly desirable, it may not be possible to require that level of mathematics and satisfy all the other requirements of an undergraduate degree. We therefore recommend the following minimum mathematics requirement, with the caveat that, if room is available, additional mathematics courses would be a desirable addition.
CS105. Discrete Structures I
CS106. Discrete Structures II
A minimum of one additional mathematics elective, chosen to support the interests of the student and the advanced electives that are used to complete the program
We have specified the two-semester approach to discrete mathematics because the topics covered in these courses are the most important area of mathematics for computer science majors. Currently, most schools offer a one-semester course. However, there is now so much material to be covered that a two-semester sequence can be far more effective than a single course.
The third required mathematics course is not specified. Instead, it should be selected in conjunction with the student's advisor based on the interests of the student and the advanced courses they plan on taking. It might include more advanced calculus, linear algebra, mathematical logic, mathematical modeling, or numerical analysis. Introductory computer science courses For the introductory computer science courses, we recommend either of the following two-course sequences described in Chapter 7:
or Both of these introductory sequences focus on important conceptual issues, such as problem solving, design specifications, and language paradigms, rather than the syntactic details of a specific programming language. Either sequence would be a good fit with a small department curriculum because they both introduce students to many fundamental ideas and enduring concepts in a small number of classes. Intermediate computer science courses For the intermediate course sequence, we selected the compressed approach presented in Section 8.2.2. This model contains five required courses that cover all 280 hours of required core material. These five courses are:-
CS210C. Algorithm Design and Analysis
CS220C. Computer Architecture
CS226C. Operating Systems and Networking
CS262C. Information and Knowledge Management
CS292C. Software Development and Professional Practice
- Exposing the student to advanced material beyond the core
- Demonstrating applications of fundamental concepts presented in the core courses
- Providing students with a depth of knowledge in at least one subarea of computer science
As with the number of required mathematics courses, the exact number of electives in a given program will typically be a function of how much room is available in the curriculum, as well as college distribution requirements. However, the number of electives should be large enough to provide depth in at least one subarea of computer science. We propose a minimum of three advanced electives, while realizing that some schools may enlarge or decrease this number based on local conditions. We feel that three elective courses can provide sufficient opportunity for depth of study while keeping the overall program to a manageable size.
To ensure that students develop a reasonable level of depth in at least one subarea, it makes sense to require that a minimum of two out of three electives be chosen from a single area within the body of knowledge. The advanced courses are listed by area in Figure 9-1. Capstone project
The final component of this curriculum model is CS490, Capstone Project. This course provides students with opportunities to enhance skills that may not be easy to accomplish in the traditional classroom setting, such as working in teams, interacting with users, developing formal problem specifications, reviewing the research journals, building prototypes, scientific writing, and making oral presentations.
The most popular model for a capstone is a team-oriented, software engineering effort in which students design a solution to an information-based problem and work in teams to implement that solution. However, there is another model that might be more attractive to outstanding students who are thinking about graduate study and research, as opposed to private-sector employment. For these students, an alternative capstone format is a research experience that includes some original work, a review of the scientific literature, and an investigation of a proposed solution, followed by a scientific paper and/or an oral presentation of the results. It is important to remember that these are undergraduates and be realistic about the amount and quality of research expected. Even so, it may be more worthwhile to expose outstanding students to the challenges of research than to have them design and build yet another program.
Finally, each school must determine how long the capstone project will last. To truly get the most out of it (especially a research-based capstone) a year-long project is extremely beneficial. However, the resources available to a small department may constrain the project experience to a single semester.
9.4.4 Programs for two-year colleges
In the United States, a large fraction of computer science students begin their studies in two-year colleges rather than at four-year institutions. As a result, computer science programs in these institutions are a critical target audience for the Computing Curricula 2001 project. Because two-year colleges have specific characteristics and concerns that are in some respects different from those of four-year programs, the CC2001 Task Force -- in conjunction with the Two-Year College Committee of the ACM and its newly formed counterpart in IEEE-CS -- has decided to publish a separate report that offers more specific recommendations for the two-year college community.Even though the recommendations for two-year colleges are included in a separate report, there are several aspects of the two-year college model that are important for U.S. four-year institutions as well. The central concern that links the programs in two- and four-year institutions is that of articulation, which refers to the process of determining how two-year college students can make an effective transition to a four-year model to complete their undergraduate study. The issue of articulation is extremely important for four-year institutions that accept students from the two-year schools and is therefore worth some discussion in this report.
Programs at two-year colleges generally fall into one of two categories -- career or transfer -- depending on the nature of the institution and the needs of local industry. A career program typically provides a broad educational foundation as well as the specific knowledge, skills, and abilities needed to proceed directly into the work environment. Students graduating from a two-year career program typically enter the work force immediately. Once they have gained work experience, some graduates of career-oriented programs may return to a four-year institution to complete their undergraduate degree, and some may move immediately in that direction. In a transfer-oriented program, most students are expected to transfer to a four-year program. Unless the two-year curriculum was specifically designed to enable such transfers, however, students will often need to take additional courses at the introductory or early intermediate levels.
Careful articulation of courses and programs between two- and four-year institutions greatly facilitates the transfer of students from one institution to the other. The overall goal of articulation is to make that transfer process as seamless as possible. Efficient and effective articulation requires accurate assessment of courses and programs as well as meaningful communication and cooperation. That articulation process, however, is complex for the following reasons:
- Students at two-year colleges are likely to come from outside the traditional student population and therefore have a greater variety of experiences then their four-year counterparts.
- Because many two-year college curricula offer internship or coop programs, the background of students from two-year colleges often contains a blend of theory and practical skills that may be difficult to map into a traditional four-year program.
- Courses do not always correspond on a one-to-one basis in the two-year and four-year programs. Even so, it is often possible to identify a sequence of courses in one institution that matches a sequence in the other, even though the number of courses in the two sequences may differ.
Faculty of both institutions must ensure that programs are clearly defined, that program objectives are followed responsibly, and that students are evaluated effectively against these defined standards. When program exit points are specified in an articulation agreement, faculty at the two-year institution must cover sufficient material to prepare students to pursue further academic work at least as well as students at the four-year institution.
A fully articulated transfer program typically provides a path into a four-year program and sufficient coursework to prepare the students to take advanced courses in the four-year program. As a result, transfer student are able to enter the four-year program as juniors, right along with their counterparts who started at the four-year school. We believe that institutions that base their early curricula on the models presented in Chapters 7 and 8 will be well positioned to design effective articulation programs that enable such smooth transitions.
 |
CC2001 Report
December 15, 2001 |
 |
