When negotiators feel they have a good understanding of each other, their interests and their goals, and have a good grasp of where they differ on the issues being negotiated over, it is time to move on to finding ways to meet the aspirations of the two parties and enable them both to achieve a good outcome. The negotiators have the choice of finding solutions through being creative or through the more competitive value-claiming end-game. In every negotiation there is, necessarily, a value-claiming phase where value is distributed among the parties. (This exchange phase will be discussed in Chapter 7.) Effective negotiators will delay value claiming to first explore what value can be created. The value that is the subject of any negotiation is often referred to as a pie; when we engage in exploration we try to increase the size of the pie before deciding how to divide it up. Negotiators don’t have to look to create value in order to come to an agreement and so may be tempted, in the interests of saving time or due to lack of skill, to skip over this exploration phase. The result is that potential for value is not uncovered, and value is ‘left on the table’.

The main metaphor of cognitive psychology is a computer metaphor, explains Bruner who, along with Piaget and Vygotsky, is one of the three most important cognitive psychologists whose theories have implications for theories of learning. The chapter describes how this computer metaphor is basically an information-processing metaphor, a comparison that seeks to clarify how information is modified, stored, and retrieved. Bruner’s model deals with how the mind has evolved to make symbolic representation possible, how concepts (categories) are formed, and how, as a result, we are able to go beyond the information given. Piaget’s developmental theory describes how assimilation and accommodation make adaptation possible, leading to the development of the cognitive skills and capabilities required for progressively more advanced forms of thinking. And Vygotsky champions the role of culture and language in cognitive development. The chapter emphasizes the clear pedagogical implications of each of these theories. It also makes the point that these three theorists were leaders of the so-called cognitive revolution, bent on replacing behaviorism.

Pavlovian explanations of learning, anchored on the principle of continguity of stimulus and response events, have proven to be highly useful in accounting for various forms of learning including the learning of conditioned emotional reactions (CERs). But these explanations fail to consider the extent to which the consequences of what we do affect our behavior. Enter Edward Thorndike who, through his law of effect, recognized that behaviors followed by positive contingencies (a satisfying state of affairs) are more likely to be repeated and learned. Conversely, those followed by more negative contingencies are less likely to be repeated. This made a great deal of sense to Clark Hull, who dreamed of developing a massive, formula-based system that could be used to explain and predict all human behavior. It was an ambitious project that didn’t quite succeed, there being too many unknown variables involved. In this chapter, while explaining and clarifying the theories of Thorndike and Hull, Mrs. Gribbin deletes an indelicate expression that had been used in earlier editions as an antidote to symbol shock. Her footnoted interruption serves the same purpose.

The final chapter summarizes and synthesizes all previous chapters, trying not to lie or to oversimplify. It begins with an account of historical and contemporary approaches to studying human learning and a review of the two major approaches to learning theories: behaviorist and cognitive. It then summarizes the behaviorist theories covered in the first chapters, looks at the transition from behaviorist to more cognitive approaches, and briefly recapitulates the main cognitive theories covered in the middle chapters. It then sums up material on memory, motivation, emotions, social learning, artificial intelligence, and machine learning. This chapter, as Mrs. Gribbins notes, is really the skeleton of the entire book, the emperor without his (or her) clothes. It ends with a synthesis, appraisal, and integration of the book. In the end, it makes the point that although historically, the search has been for one best way of explaining human learning and behavior, there are actually many ways of learning, many different models of the learner, and perhaps the need for many different explanations.

As Mark Twain put it, “Persons attempting to find a motive in this narrative will be prosecuted.” Sorry, Mark, there is a motive in this chapter’s narrative and we are now beyond the statute of limitations for your intended prosecution. The overriding motive is to illustrate how current explanations of what moves and directs human behavior are mainly cognitive. Earlier explanations, detailed in the first pages of the chapter, dealt with needs and drives, reflexes, and instincts, tendencies toward hedonism and eudemonic goals (Maslow’s self-actualization), and a need to maintain an optimal level of arousal. Current social/cognitive views of motivation look at how the ability to anticipate, to evaluate, to foresee consequences, to determine personal goals and develop intentions based on the values and costs associated with these goals contribute to an intriguing personal calculus that underlies many of our most important behaviors. These are key concepts, the chapter argues, given that one of the important goals of the educational enterprise is to develop self-regulated learners – learners who set their own goals, select and develop strategies to reach them, and implement and monitor these strategies, changing them as necessary.

New ideas seldom appear completely out of the blue, says Mrs. Gribbin when introducing the sixth chapter. She explains that long before their appearance, there are usually hints that new ideas are coming. So it was with cognitivism. This chapter looks at three distinct theoretical approaches that reflect the behavioristic notions that preceded them while foreshadowing the more mentalistic, cognitive positions that followed. Hebb’s speculation about the neurological basis of higher mental processes in the form of cell assemblies and phase sequences is based on behaviorist theory but opens the door to speculation about thinking. Tolman’s argument that even the behavior of the lowly rat, usually explained using conditioning principles, is nevertheless purposeful reflects a clearly cognitive orientation. And the Gestalt notion that learning is not so much a matter of reinforced trials and errors but more a question of insight in the struggle to perceive whole, meaningful, and satisfying patterns also reveals a cognitive inclination. The chapter illustrates how the machine-like metaphors of behaviorism reflected the conviction that explanations should be tied to observable events. The metaphors of cognitivism are less literal: They are metaphors invented for structures that cannot so easily be observed and described.