Cognitive Apprenticeship and Instructional Technology
Allan Collins Bolt Beranek & Newman Inc., Cambridge, MA
In earlier times, practically everything was taught by apprenticeship: growing crops, running trades, administering governments. Schools are a recent invention that use many fewer teaching resources. But the computer enables us to go back to a resource-intensive mode of education, in a form we call cognitive apprenticeship ( Collins, Brown, & Newman, 1989). As we argued in Collins, Brown, and Newman ( 1989), cognitive apprenticeship employs the modeling, coaching, and fading paradigm of traditional apprenticeship, but with emphasis on cognitive, rather than physical skills. My basic thesis in this chapter is that technology enables us to realize apprenticeship learning environments that were either not possible or not cost-effective before.
This chapter addresses the questions: What kind of leverage do we derive from computer technology, and what design criteria can we specify for building computational learning environments? We have developed a tentative set of characteristics ( Collins, Brown, & Newman, 1989) that we think computational learning environments should have, based on analyzing what kinds of tutoring systems we see emerging, what we have learned from studies such as Lampert ( 1986), Palincsar and Brown ( 1984), Scardamalia, Bereiter, and Steinbach ( 1984), and Schoenfeld ( 1983, 1985), and what resource-rich learning environments (such as tennis coaches and graduate school instruction) are like.
This chapter discusses six characteristics of cognitive apprenticeship for which technology provides particular leverage. For each abstract characteristic, I address: