20.6 Conclusion

In our previous review of cognitive teaching models (Wilson & Cole, 1991), we were surprised by the diversity of approach and method. In this review, key differences again should be acknowledged between the various models. Cognitive load theory adopts a no-nonsense approach to the efficient and effective teaching of defined content. The packaged computer-based learning environments (Sherlock and the case-based scenarios) are highly effective, controlled environments that filter out much of the world's complexity and provide learners with an authentic-enough environment conducive to learning. The problem-based learning model is simpler in design yet more ambitious in the sense that it departs more radically from established instructional methods. Finally, the tools and models related to learning communities become almost antimodels in the sense that so much is left to the participants, both instructors and students.

In view of the substantial differences between models, generalizing across them is a difficult task. Several key points of reflection, however, are offered below.

1. Learning from implementation as well as design. There is no doubt that developing and trying out coherent models can yield important outcome information. Knowing, for example, that reciprocal teaching produces, on average, effect sizes of .32 on standardized tests and .88 on locally developed measures (Rosenshine & Meister, 1994) conveys a sense of confidence and reliability for users of the method. At the same time, some of the most valuable lessons learned may come from the real-world experience gained in setting up and administering a program. The implementation can be just as important as the theory-guided design.

An example may be taken from the 1970s research in computer-assisted instruction. One program, the TICCIT project, was shown by an NSF evaluation to achieve its objectives more successfully than traditional classroom instruction (Merrill, Schneider & Fletcher, 1979). The program failed, however, in getting students to stay with the program; the dropout rate was unacceptably high when compared to traditional classrooms. In this case, the actual development and tryout of working models produced knowledge that would not have been anticipated ahead of time.

Another example is Clancey's Guidon-Manage research in intelligent tutoring systems (see 19.3, 19.4), or ITS (1993). In a remarkable example of self-reflection, Clancey concludes: "After more than a decade, I felt that I could no longer continue saying that I was developing instructional programs for medicine because not a single program I worked on was in routine use..." (p. 7). What did Clancey learn from his research? Apart from his contribution to intelligent tutoring technologies, he learned that research in a laboratory differs from research in the field. "[Researchers must participate in the community they wish to influence ... (p. 9, italics retained). "As ITS matures, some members of our research community must necessarily broaden their goals from developing representational tools to changing practice - changing how people interact and changing their lives ... (p. 9, italics retained). Clancey then reflects on how he might approach the

Guidon-Manage research differently today:

• Participating with users in multidisciplinary design teams versus viewing teachers and students as my subjects
• Adopting a global view of the context ... instead of delivering a program in a ... box
• Being committed to provide cost-effective solutions for real problems versus imposing my research agenda on another community
• Facilitating conversations between people versus only automating human roles
• Relating ... ITS computer systems to ... everyday practice ... versus viewing models ... as constituting the essence of expert knowledge that is to be transferred to a student
• Viewing the group as a psychological unit versus modeling only individual behavior (Clancey, 1993, p. 17)

Although the specific research agenda is different, Clancey's lessons learned apply very well to cognitive teaching models. Developers of teaching models need to stay close to the context of use and include implementation within their domain of interest.

Like the TICCIT and Guidon projects, outcomes of research are sometimes negative, for example, the failure of young students to learn abstract concepts via Tabletop, or the tendency for some experienced medical students to become bored with PBL activities. We believe that these negative findings can become extremely useful as formative evaluation data, feeding back into future implementations of the model.

Norman (1993) speaks of the power of representation as a stimulus to scientific progress. Repeatedly in the history of science, revolutionary strides are made when a new technology is developed that allows a repicturing of problems in a domain. By analogy, a similar kind of progress is made possible by research on teaching models. Through the careful articulation and construction of actual working methods, new perspectives are made possible. An actual product, once created, may be examined from a variety of angles and for a variety of purposes, many perhaps unintended by the creator. Determining exactly "what is learned" from research of this type may be difficult to articulate yet remain extremely valuable to the scientific and practitioner communities.

2. Deciding on a model is closely tied to the curriculum question. Perkins (1992b) warns of a common fallacy implied by the statement: "What we need is a new and better method. If only we had improved ways of inculcating knowledge or inducing youngsters to learn, we would attain the precise ... outcomes we cherish" (p. 44). Instead, Perkins believes that "given reasonably sound methods, the most powerful choice we can make concerns not method but curriculum-not how we teach but what we choose to try to teach" (p. 44). This comment suggests that a fundamental step in instructional design involves the serious consideration of learning goals. A variety of constituencies should be included in this process, including sponsors and members of the learning community itself. Once consensus is reached about the kind of learning being sought, certain teaching models become unfeasible while others become more attractive.

A basic lesson learned from observing schools is that two teachers may be covering the same ostensive curriculum while what really is taught differs radically between them. And what any two students learn in the same teacher's class may differ just as radically. At its base, the constructivist movement in education involves curriculum reform, a rethinking of what it means to know something. A constructivist curriculum is reflected in many of the models reviewed in this chapter. Thus, if a commitment is made toward rethinking curriculum to expand the roles of knowledge construction and learning communities, then a corresponding commitment needs to be made in rethinking learning activities. Deciding on a teaching model is not a value-neutral activity. Recognizing this puts the selection of a teaching model squarely into the political realm of policymaking. New issues become important, such as access, equity, representation, voice, and achieving consensus amid diverse perspectives.

As Reigeluth (1983) acknowledges, curriculum and instruction cannot be completely separated. There is a tendency among many institutions to give lip service to higher-order outcomes while maintaining teaching methods that specifically suppress such outcomes. Medical schools that teach students to simply memorize and take tests are an example. Another example is a military school whose mission statement prizes "creativity" in students, yet whose teaching methods and authoritarian culture strictly reinforce conformity and transmission of content.

3. Deciding on a teaching model and making decisions within that framework are highly situated activities. The success of a given implementation will depend more on the local variables than on the general variables contained in the various models described above. Put another way, "the devil is in the details." There is a way to succeed and a way to fail using a whole host of teaching models. All the models reviewed above can succeed if properly implemented. Teachers and students must see the sense of what they are doing, come to believe in the efficacy of the program, and work hard to ensure that the right outcomes are achieved.

This situational perspective conflicts with traditional views. Thinking of instructional design as a technology would lead us to think that a situation gets analyzed, which leads to a technical fix to be implemented, which leads either to a measured solution to the problem or a revision in the fix for the next cycle of intervention. A situated view of instructional design would lead to a different process:

A. A learning community examines and negotiates its own values, desired outcomes, and acceptable conventions and practices.

B. The learning community plans for and engages in knowledge-generating activities within the established framework of goals, conventions, and practices.

C. Members of the learning community, including both

teachers and students, observe and monitor learning and make needed adjustments to support each other in their learning activities.

D. Participants occasionally reexamine negotiated learning goals and activities for the purpose of improving learning and maintaining a vital community of motivated learners. This may lead to new goals and methods and cultural changes at all levels, from cosmetic to foundational.

This situated, community-oriented view of instruction takes a more holistic view to the design of instruction. The community is opportunistic in addressing "design" issues at any stage of planning and implementation. Community members, including students, have a voice in determining what happens to them in instruction. In return, they must show the needed commitment and disposition to behave responsibly and in support of learning.

If community members have participated in the establishment of a program, they are more likely to believe in it. If they believe in the program, the chances of success increase dramatically. As Perkins (1992b) suggests, even very imperfect instructional methods can work if the commitment is made to work together and ask the right questions in designing curriculum.

4. Each teaching model is a particular blend of costs and outcomes. Some kind of costs-benefits analysis - implicit or explicit - happens in designing educational programs. Surveying our teaching models reveals that some have demonstrably high development costs. Sherlock has taken a decade of patient research to achieve its present form. Once developed, however, the prototype model may be replicated at a reasonable cost. Other models, such as problem-based learning, may pose heavy demands in terms of time in the curriculum. Instructional designers (or learning-community members) must then face the question of how and whether to implement such resource-demanding teaching methods into an existing system and curriculum.

Every decision to adopt one teaching model over another involves such weighing of pros and cons. However, while costs may be objectively measured and estimated, learning benefits are notoriously difficult to reduce down to a number. This inequity of measurability results in a common bias: The cost differences become exaggerated, while the potential benefits, because they are harder to measure, tend to be undervalued or ignored. Comparison of alternative teaching models must give full consideration to qualitative differences in learning outcomes, in addition to the more visible cost differences in time and money.

Some ideas may be borrowed and inexpensively incorporated into related products or programs. For example, if an instructor becomes excited by Schank's case-based scenarios, she may choose to incorporate case histories and classroom simulations into her teaching. While the resulting lessons may bear only a passing resemblance to the computer-based scenarios, they are heavily influenced by Schank's principles of case-based, interactive instruction. Many of the principles discussed above, including those of cognitive apprenticeships and intentional learning communities, can be efficiently adapted into instruction in a number of ways, depending on local circumstances and resources.

5. Instruction should support learners as they become efficient in procedural performance and deliberate in their self-reflection and understanding. Virtually all of the teaching models under review-Sweller's research notwithstanding - emphasize the grounding of instruction in complex problems, cases, or performance opportunities. Yet organizing instruction around problems and cases should not mask the importance of perception, reflection, and metacognitive activity. Indeed, these two aspects of human performance (problem solving and perception) can be seen as inherently complementary and equally necessary. Contrary to the suggestion of Dreyfus and Dreyfus (1986), experts are more than mere automatic problem solvers. Rather, experts become experts through a progressive series of encounters with the domain, each involving an element of routine performance and a corresponding element of reflection and deliberation. This is the process of expertise spoken of by Scardamalia and Bereiter (1994) and discussed above.

Prawat (1993) makes this point well. While there is a tendency among cognitive psychologists to make problem solving central to all cognition, Prawat reminds us that schemas, ideas, and perceptual processes hold an equally important place. Learning how to see is as important as solving a problem once we do see. Principles of perception-whether from ecological psychology (Allen & Otto, Chapter 8), connectionism, or aesthetics-need to have a place within successful teaching models. This includes teaching students how to represent problems and situations, but also how to appreciate and respond to the aesthetic side of the subject, how to reflect upon one's actions, and how to "raise one's consciousness" and recognize recurring themes and patterns in behavior and interactions.

6. Successful programs must seek to make complex performance do-able while avoiding the pitfalls of simplistic proceduralization. The art of "scaffolding" complex performance is a key problem area that surprisingly is still not well understood. How does a coach entice a young gymnast to perform just beyond her capacities, overcoming the fear and uncertainty that normally accompany new performances? How does the coach know just when and where to step in, preserving the integrity of the task (and the learning) while not letting the athlete fall on her head? These are questions of appropriate scaffolding or support for learning. Once a teacher begins believing the constructivist agenda and the importance of authentic, meaningful tasks, then the challenge of supporting novice performance within a complex environment becomes a central concern. As Sweller's research makes clear, poorly supported problem-solving activities force learners to rely on weak methods that they already know. Appropriate and wise scaffolding makes problem-solving activities more efficient because learners stayed focused within the critical "development' zone between previously mastered knowledge and skills beyond their reach. Developing a technology for optimizing this kind of support is an area in need of further research and development.

This same concept of scaffolding can be directed to the implementation of the teaching model itself. Instructional designers and teachers need proper supports and aids in designing according to a particular model or tradition. At the same time, they should be cautioned against simplistically "applying" a model in a proceduralized or objectivist fashion. Postmodernists would say that in such cases, the model "does violence" to the situation. The complexities of a situation should not be reduced down to the simple maxims of a teaching model. Any model that is forced on a situation and made to fit will lead inevitably to unintended negative consequences. The negative fallout will happen at those points of disjuncture or lack of fit between model and situation. As we have stressed, the details of the situation need to be respected and taken into account when adapting a model to a situation.

This, perhaps, is a more appropriate way of thinking about implementation: Rather than applying a particular teaching model, a teacher necessarily adapts that model to present circumstances. Learning how to adapt abstractions to concrete realities is a worthy task for both students and teachers, and, indeed, may lie at the heart of some forms of expertise.

Each of these points is worthy of continued research. As psychologists continue to develop models for teaching that embody their best thinking and theories, the field of instructional design will have opportunities for reflection and growth as they reexamine their own models and methods. Our hope is that the dialogue may continue to flourish and expand, resulting in a "transformation" of both communities.