Slightly more than a decade ago we published a book, Rethinking Religion: Connecting Cognition and Culture, in which we launched the cognitive science of religion. For all of the froth that accompanies encounters between the humanities and the cognitive sciences on university campuses, everyone knows that the best work in each area regularly looks to the other for inspiration and correction. Our goal is not to supplant traditional work in religious studies but to supplement it. If our work seems tilted too far toward the scientific, it is only because we aim to redress an imbalance -an imbalance in strategy and approach that favors the particular over the general, the idiosyncratic over the systematic, and the interpretive over the explanatory (as if we could make sense of either item in each pair in isolation from the other). What we are out to do is to help bring an end to the defensive pronouncements of humanists and, especially, of scholars of religion concerning what the sciences can never address productively. Who knows what the sciences can or cannot address productively? Only time and a great deal of hard work will tell.

We should emphasize that this aspiration is not born of any undue confidence about the truth of the proposals we advance. (What we take up are, after all, empirical matters.) What should be most striking are the tremendous difficulties connected with even articulating testable theories in these domains, let alone testing them.

Chapter overview

We aim to show how the considerations of ritual form our theory emphasizes motivate an account of general evolutionary trends in religious ritual systems that affect the distributions of these cultural representations. Toward that end, our principal goal is to show how a small set of psychological variables exert selection pressures on all religious ritual systems, and how those systems' resulting properties insure that they meet the mnemonic and motivational demands necessary for their transmission. Well-adapted ritual systems are ones that cope with the constraints these psychological variables impose.

Nothing about this analysis will depend upon any of the details about either the Pomio Kivung or the Dadul-Maranagi splinter group. We continue to devote attention to them, because they serve as a means for highlighting differences between our and Whitehouse's views and because they so splendidly illustrate one of the dynamical profiles our analysis identifies. Although, finally, we will maintain that the materials from Whitehouse's ethnography constitute an exceptional case in some important respects, it is for just that reason that they will serve so well in explicating other patterns. Studying atypical cases in order to illuminate the workings of the typical ones is a standard research strategy in science.

It is uncontroversial that the general evolution of both the Dadul-Maranagi splinter group's ritual innovations and its innovative rituals was toward higher levels of sensory pageantry.

Paradoxes, puzzles, and explanatory problems

Some rituals captivate the imagination. Others provoke boredom.

We are easily moved, often excited, and occasionally even astounded by the sights, sounds, and smells accompanying ritual spectacles. These events stimulate our senses, enliven our emotions, and captivate our minds. The enthronement of popes, the inauguration of presidents, the burial of heroes arrest our attention and embed memories that last a lifetime. Everyone loves sensory pageantry. Some rituals focus the attention, feed the imagination, evoke the remembrance of things past as well as the desires of things to come, and inspire dramatic actions that stand out against their everyday background. Yet the salience of such dramatic spectacles should not obscure the fact that “ritual” often refers to the repetition of small and thoroughly mundane acts. Even though these rituals break with the ordinary world too, they frequently remain thoroughly humdrum. They trigger automatic responses that appear to be completely mindless. If we focus on participants' psychological responses in ritual situations, we cannot fail to notice the different degrees of emotion involved in these two sorts of cases. Some rituals are so emotionally arousing that their effects seem to last forever. In other rituals emotion seems to play little, if any, role.

Compare, for example, the comparatively lavish preparations for weddings and their impact on the participants' emotions with the more modest accouterments and emotional responses connected with routine blessings. The weddings quite regularly involve special music, clothes, foods, and more.

Since memories are found in scenes, a very important part of memory organization is our ability to travel from scene to scene. A MOP is an organizer of scenes. Finding the appropriate MOP, in memory search, enables one to answer the question, What would come next? when the answer is another scene. That is, MOPs provide information about how various scenes are connected to one another. Finding a MOP is not a conscious process. We don't sit around saying to ourselves, “I wonder what MOP would work well here?” But, we do seek to know where we are, what's going on, and what method there is to the madness we have just encountered. This means knowing what scene we are in and what scene is coming next.

Most of the MOPs I have discussed so far have been physical MOPs. They can contain scenes that seem societal in nature, but what is actually happening is that one scene is being governed by two MOPs. Thus, for example, both M-CONTRACT, which is a societal MOP, and M-AIRPLANE, which is a physical MOP, share a PAY scene. Paying can be seen as both a physical event and a societal event. The physicalPAY scene from AIRPLANE may exist and contain memories if you bought your ticket at the airport.

At the root of our ability to learn is our ability to find the experience we have in our memory that is most like the experience we are currently processing. Most learning doesn't look like learning at all. For instance, consider a situation in which we drive down a road and remember to take the first right after the public library. We do not seem to be learning; we simply feel we're either following directions (if this is the first time we have taken this particular trip) or recalling (if we have made this trip before). But, in either case, we are learning. On the other hand, consider a situation in which someone gives us directions, we try to memorize them, and then say we have learned the way to a place. Because we have been socialized in a particular way, this feels like learning. Understanding why the former situation is learning (even if it doesn't seem like it) and the latter is not (even if it does seem so) is critical to understanding the nature of the comprehension process and its modification through experience. Memorizing is not learning in any real sense.

Imagine you are a small child and your parent believes you should learn how to make toast. Your parent can sit you down and give you a lecture on the art of toasting, but this is probably not the best way to teach you.

Developing Structures

People have widely differing experiences and must deal with a variety situations in the world. To keep track of these things, each person must create and maintain his own memory and processing structures. No one single set or configuration of structures can be used to explain the diversity of understanding and skills that we see in the world. It seems quite unlikely, then, that any particular structures are innate, though the ability to form and manipulate such structures may very well be.

No two people are likely to have identical structures except when those structures reflect the physical nature of the world or when those two people must function in identical societal arrangements. Even then, our individual experiences alter our view of the world to such an extent that we can still expect major differences. Each person's mental structures will contain distinct personal experiences and different expectations. Thus, we can expect people to have rather idiosyncratic TOPs, MOPs, scenes, and scriptlets. How do these structures get built in the first place? How do existing structures get altered once they have been built? How do new structures get created out of a reorganization of old structures?

To build our own memory structures, we must be able to recognize that a current experience is in some way similar to one that has occurred previously and we must be able to focus on the important aspects of both episodes and eliminate from consideration those aspects of the current situation that are irrelevant to the retrieved memory.

Memory is a morass of complex structures, related by the episodes they point to and the temporal and causal connections between them. Learning means the augmentation and creation of such structures. Through experience, memories become useful containers of expectations about the world. But practice isn't the only thing needed to help people learn. Teaching becomes increasingly important as the level of abstraction required becomes more complex. Encouraging a student to see one experience as a variant of another is a key issue in teaching (Gholson et al., 1996; Bransford et al., 1989), as is encouraging the repetition of events that must be learned by practice. We learn through experience, reflection, and explanation, each of which helps us build the abstract memory structures we need.

The Nature of Understanding

Two people can have the same experience, yet encode it differently. They can see the same thing as confirmation of quite different beliefs, because we see in terms of what we have already experienced. The structures we have available in memory are an embodiment of our experiences, and we understand new experiences in terms of our prior structures, which reflect how we have understood things in the past. Thus, it is critical to carefully reflect upon the nature of memory structures.

In Chapter 2, I discussed how a Burger King trip might remind someone of McDonald's. What kind of reminding is this? There are two possibilities.

Learning to learn is a very common phrase these days. I don't like it much because we know how to learn from birth. We build MOPs and TOPs effortlessly, and we respond to expectation failures automatically by building explanations. The phrase “learning to learn” refers to the idea that learning to do any specific thing is really not all that relevant. The real issue is to get students to the point where they are excited about learning and they want to learn more because doing so is fun. Children (and adults as well) must also believe they can learn. This is often a big problem with kids' internalizing failure in school into an idea that they just are not smart enough (Eckert, 1989). They don't need to learn to learn – they simply need to rely upon the natural learning mechanisms they were born with.

Attitude is critical to continued, lifelong learning and to the development of a keen intellect. People who are closed to new ideas and are unwilling to think cannot really be very intelligent; such people may have had dynamic memories but have gradually become impervious to change. In order to understand what intelligence is and what it is not, we need to get away from the problem-solving view of intelligence (which defines intelligence in terms of how well we have learned how to apply rules we were explicitly taught) and move over to one oriented more toward case-based reasoning, which is the natural outgrowth of a dynamic memory.

All real learning involves learning by doing. But, do we know what we are learning when we learn by doing? At first glance, learning seems to be a conscious process. We tell people things, they hear them, and they learn them – consciousness, pure and simple. The idea that we learn by being told is pervasive in discussions of learning (Strauss and Shilony, 1994). Nevertheless, most of what we know of any importance in our daily lives is actually nonconscious. Furthermore, it seems fairly obvious that we don't learn nonconscious stuff consciously. The distinction between nonconscious and conscious learning is thus an important one to explore.

Most conceptions of knowledge involve an approach that implies that we know what we know. Following this is the idea that we can teach that knowledge by simply telling people what we want them to know (diSessa, 1982; Bruer, 1993; Bransford et al, 1989). To some extent this is true. For instance, we learn multiplication tables by memorizing them. But memorization doesn't provide much knowledge that is of real value. Proponents of learning by doing (as opposed to learning by being told) have long lamented the school system's lack of understanding regarding the idea that people learn by doing as their primary way of learning.

Can we truly educate people? This seems like an odd question for those who believe intelligence is immutable. But for many who study the mind, it is not so odd. One reason our school systems are in such difficulty is that the underlying assumption of “just fill them with facts” comes from an idea that intelligence is not mutable. In this view, people can know more, but they can't really change how they think.

The dynamic memory view is that intelligence is, of course, mutable. If intelligence depends upon the creation of MOPs and TOPs and other types of generalizations, then it follows that helping students create explanations and generalizations and find patterns helps them to know more and to be more intelligent – not to know more in the “Trivial Pursuit” sense of acquiring facts, but to know more in a deep sense. Knowing more, in a deep sense, is truly a change in intelligence – it is the ability to better comprehend the world in which we live.

Modern educational practice has been greatly influenced by trends in academic psychology. Behaviorism, for instance, inspired a large industry devoted to turning out educational products that put into practice what the theory proposed. Of course, given the inevitable time lag in the popular dissemination of such trends, by the time this industry hit its stride, behaviorism was already in retreat as a theoretical framework for psychology. Unfortunately, by then the damage had been done.

Much of our ability to understand, and to be creative and novel in our understanding, is due to our ability to see connections and to draw parallels between events. Of course, when the parallels drawn are between one episode of eating in a restaurant and a similar episode, our work doesn't seem creative, even though it results in a new idiosyncratic mental structure. Drawing parallels between events in one arena and those in a very different context seems more creative. We can recognize that what we have learned to do in one situation may apply in another.

When a person acts stupidly in one situation and suffers the consequences, we expect him to learn from his experiences. We find it hard to understand why he would repeat the same behavior in a new, but similar, circumstance. The kind of learning from experience we expect of people comes from our belief that they can and do recognize similarities in situations.

I used this argument in previous chapters as a justification for structures like MOPs. But even MOPs are too specific. As noted in Chapter 4, we often get reminded across situations that have only very little in common on the surface. Thus, there must be structures that capture similarities between situations that occur in different domains and, furthermore, these structures must be able to capture similarities that are far deeper than those on the surface.

Every aspect of human behavior involves the pursuit of goals. Sometimes these goals are rather simple, like brushing your teeth to prevent decay. Sometimes they are quite unconscious, like having your mind search for similar experiences when you encounter some new experience. And, sometimes they are quite complex, like trying to build high-quality educational software as a means to effect change in the school system.

When goals are simple, we really don't think about them much. When they are unconscious, we don't think about them at all. And, when they are complex, we may think about them, but find the going so rough that we hone in on the simplest ones and lose the forest for the trees.

Understanding how people pursue goals is a critical aspect of understanding cognition. For computers to really understand human stories, they would need a complete model of the goals people pursue: the plans, the use, and the complexities that arise. The issue is this: If goals underlie human behavior to the extent that we cannot understand a story or what someone says or wants, without a clear assessment of the underlying goals and the interaction of those goals, then it follows that goals are at the root of human learning. Why would anyone learn anything if not to help in the pursuit of a goal? Why would anyone try to understand anything if not because he had the goal of learning new information from what he was trying to understand?

When we begin to think about learning, we begin immediately to ask about knowledge. It is very difficult to think about education without thinking about the knowledge we want to impart to students. We live in a world in which knowledge reigns supreme. In the popular culture, games like “Trivial Pursuit” capture the country's attention; television focuses on “Jeopardy” and other “knowledge games” that test who knows what. Far more important, school focuses on the same sorts of “trivial” knowledge. Schools are driven by tests that focus on fill-in-the-blank and multiple choice questions, thereby making success in school dependent upon memorization of facts. Even outside of school, in the workplace, companies train employees to do their jobs and then worry how to assess what the employees have learned (Brinkerhoff and Gill, 1994). The need to assess has focused everyone on things that are assessable. Thus facts have become “the currency of the educated” because they are so easy to measure.

The problem with all this is twofold. When our institutions of learning focus on test results, it follows that they need to focus on teaching what is testable. This leads to throwing out the baby with the bath water. The question of what to teach gets perverted by the measurements that are already in place, thus making curriculum change impossible. But, perhaps more important, there is a second problem revolving around the issue of our understanding who we are and what makes us tick.

What is a dynamic memory? It is a flexible, open-ended system. Compare the way an expert stores knowledge about books in his field to the way a library catalog system does the same job. In a library, an initial set of categories is chosen to describe a domain of knowledge. Within those categories, titles, authors, and subjects of the books are recorded. Such a system is not dynamic. Eventually, the categories will have to be changed; overutilized categories will require updating; other categories will have to be created to handle new subjects and subject divisions.

A library does not have a dynamic memory. It changes with great difficulty. More important, to change it requires outside intervention. An expert has neither of these problems. He can change his internal classification system easily when his interests change, or when his knowledge of a particular subject matter changes. For the most part, these changes are not conscious. The expert may relate one idea to another or he may fail to do so. He knows when he knows something, but there is a lot he doesn't know he knows. He may be able to categorize without knowing the categorization scheme he uses. He can make observations about what he knows and thus can alter the memory structures that catalog what he knows. He can do this without even realizing he has done it. He has a dynamic memory.