Throughout most of history, teaching and learning have been based on apprenticeship. As Rogoff (1990) makes clear, children throughout the world learn how to speak, grow crops, and make clothes by apprenticeship. They do not go to school to learn these skills; instead, adults in their family and communities show them how and help them practice. Even in advanced societies, people learn through apprenticeship, such as gaining a first language, acquiring critical skills in a new job, and doctoral training for scientists. When people have the resources and a strong desire to learn, they often hire a coach to teach them by apprenticeship, because apprenticeship is a more effective for learning. But for most kinds of learning, schooling has replaced apprenticeship.
Collins, Brown, & Newman (1989) have argued that computer-based learning environments could provide students with apprenticeship-like experiences, providing the attention and feedback that are associated with apprenticeship. Their research builds on the ideas of Vygotsky (1978), whose view of how social interaction fosters cognitive development resembles apprenticeship, in which a novice works with an expert in the zone of proximal development.
In her study of a tailor shop in Africa, Lave (1988) identified the central features of traditional apprenticeship. Learning is instrumental to the accomplishment of meaningful real-world tasks and embedded in a social and functional context. The apprentice observes the master modeling the target process. The apprentice then attempts to execute the process with coaching from the master. A key aspect is guided participation (Rogoff, 1990): the support that the master provides until the novice has acquired the needed skills. As the learner develops increasing skill, the master provides less help, eventually fading away completely.
Cognitive apprenticeship (Brown, Collins, & Duguid, 1989; Collins, Brown, & Newman, 1989) updated traditional apprenticeship to apply to subjects taught in school. The cognitive emphasizes that the focus is on cognitive skills, rather than physical ones. Traditional apprenticeship
evolved to teach domains in which skills are visible. But students lack access to the cognitive processes of instructors as a basis for learning through observation. Cognitive apprenticeship is designed to bring these processes into the open, where students can observe and practice them.
There are two other major differences between cognitive apprenticeship and traditional apprenticeship. First, because traditional apprenticeship is set in the workplace, the tasks arise not from pedagogical concerns, but from the demands of the workplace. In cognitive apprenticeship tasks are sequenced to reflect the changing demands of learning. Second, whereas traditional apprenticeship emphasizes teaching skills in the context of their use, cognitive apprenticeship emphasizes generalizing knowledge, so that itcan be used in many different settings.
Cognitive apprenticeship focuses on four dimensions that constitute any learning environment: content, method, sequence, and sociology.
Content. Experts have to master domain knowledge, the concepts, facts, and procedures associated with a specialized area. In the late twentieth and early twenty-first centuries, researchers have been identifying the strategic knowledge that supports people's ability to make use of these concepts, facts, and procedures to solve real-world problems:
- Heuristic strategies are techniques for accomplishing tasks that might be regarded as tricks of the trade; they do not always work, but can be quite helpful. Most heuristics are tacitly acquired by experts, but there have been attempts to address heuristic learning explicitly (Schoenfeld, 1985).
- Metacognitive strategies control the process of carrying out a task. Metacognitive strategies have monitoring, diagnostic, and remedial components; decisions about how to proceed in a task depend on one's current state relative to one's goals, on an analysis of current difficulties, and on the strategies available for dealing with difficulties.
- Learning strategies pertain to learning domain knowledge, heuristic strategies, and control strategies. For example, Chi and her colleagues (1989) have identified strategies students should follow to learn how to solve math and science problems.
Method. The six teaching methods associated with cognitive apprenticeship fall roughly into three groups. The first three methods (modeling, coaching, and scaffolding) are the core of traditional apprenticeship. The next two methods (articulation and reflection) are designed to help students to generalize their learning. The final method (exploration) is aimed at encouraging learner autonomy.
- Modeling involves an expert performing a task so that the students can observe the processes that are required to accomplish it. In cognitive domains, this requires externalization of internal processes. For example, a teacher might model reading in one voice, while verbalizing thoughts in another voice. In mathematics, Schoenfeld (1985) models problem solving when students bring him difficult problems to solve in class.
- Coaching consists of observing students' work and offering hints, challenges, scaffolding, feedback, modeling, reminders, and new tasks aimed at more expert performance. In Palincsar and Brown's (1984) reciprocal teaching of reading, the teacher coaches the students while they ask questions, clarify their difficulties, generate summaries, and make predictions.
- Scaffolding refers to the supports teachers provide to help students carry out tasks. These supports can take either the form of suggestions or hints, as in Palincsar and Brown's (1984) reciprocal teaching, or they can take the form of physical supports, as with the short skis used to teach downhill skiing. Fading involves the gradual removal of supports until students are on their own.
- Articulation includes any method of getting students to explicitly state their knowledge and reasoning in a domain. Inquiry teaching (Collins & Stevens, 1983) is a strategy for questioning students to lead them to articulate their understanding.
- Reflection involves enabling students to compare their own problem-solving processes with those of an expert or of other students. Reflection is enhanced by use of various techniques for replaying the performances of both expert and novice for comparison (Collins & Brown, 1988).
- Exploration involves guiding students to problem solving on their own. Enabling them to do exploration is critical, if they are to learn how to frame interesting problems that they can solve. Exploration is the ultimate fading of support.
Sequencing. Cognitive apprenticeship provides principles to guide the sequencing of learning activities.
- Increasing complexity. Tasks should be sequenced to include more and more of the skills and concepts necessary for expert performance. For example, in reading, students progress from relatively short texts with simple syntax to longer texts with complex ideas that make interpretation difficult.
- Increasing diversity. Tasks should be sequenced so that a wider variety of strategies or skills are required. As skills become well learned, it is important that the student learns to distinguish the conditions under which they apply.
- Global before local skills. In tailoring (Lave, 1988) apprentices learn to put together a garment from pieces before cutting out pieces themselves. Having a model of the overall activity helps learners make sense of the portion they are carrying out, improving their ability to monitor progress and develop self-correction skills.
Sociology. Tailoring apprentices learn their craft in a busy shop, surrounded by masters and apprentices they can talk to and observe. They engage in activities that contribute directly to the production of garments. Hence, apprentices learn skills as applied to real-world problems, within a culture of expert practice. These considerations suggest several characteristics affecting the sociology of learning.
- Situated learning. A critical element in fostering learning is having students carry out tasks in an environment that reflects the nature of such tasks in the world (Brown, Collins, & Duguid, 1989; Lave & Wenger, 1991). For example, Dewey created a situated-learning environment in his experimental school by having the students design and build a clubhouse, a task that emphasizes arithmetic and planning skills.
- Community of practice. This refers to the creation of a learning environment in which the participants communicate about and engage in the skills involved in expertise (Lave & Wenger, 1991). Such a community develops a sense of ownership, personal investment, and mutual dependency.
- Intrinsic motivation. It is important that students perform tasks, because they are intrinsically related to a goal of importance to them, rather than for some extrinsic reason, such as getting a good grade or pleasing the teacher.
- Collaboration. Exploiting cooperation refers to having students work together in a way that fosters collaborative problem solving. Collaboration is a powerful motivator and a powerful mechanism for extending learning resources.
In the years since 1989 when cognitive apprenticeship was first introduced, there has been extensive research toward developing learning environments that embody many of these principles.
Situated Learning. Goal-based scenarios (Schank et al., 1994) embody many of the principles of cognitive apprenticeship. Learners are given real-world tasks and the scaffolding they need to carry out such tasks. For example, in one computer-based scenario learners are asked to advise married couples as to whether their children are likely to have sickle-cell anemia, a genetically-linked disease. In order to advise the couples, learners must find out how different genetic combinations lead to the disease and run tests to determine the parents' genetic makeup. There are scaffolds in the system to support the learners, such as recorded experts who offer advice. Other goal-based scenarios support learners in a variety of challenging tasks, such as putting together a news broadcast or developing a computer-reservation system. Goal-based scenarios make it possible to embed cognitive skills and knowledge in the kinds of contexts where they are to be used.
Video and computer technology has enhanced the ability to create simulation environments where students are learning skills in context. A novel use of video technology is the Jasper series developed by the Cognition and Technology Group (1997) at Vanderbilt University to teach middle-school mathematics. In a series of 15- to 20-minute videos students are put into various problem-solving contexts: e.g., deciding on a business plan for a school fair or a rescue plan for a wounded eagle. The problems are quite difficult to solve and reflect the complex problem solving and planning that occurs in real life. Middle-school students work in groups for several days to solve each problem. Solving the problems develops a much richer understanding of the underlying mathematical concepts than the traditional school-mathematics problems.
Communities of Learners. In recent years there has developed a learning communities that approach builds on Lave and Wenger's (1991) concept of a community of practice. In a learning community the goal is to advance collective knowledge in a way to support the growth of individual knowledge (Bielaczyc & Collins, 1999).
Brown and Campione (1996) have developed a teaching model they call Fostering a Community of Learners (FCL) for grades 1 through 8. In the FCL model there are three research cycles per year. A cycle begins with shared activities to build a common knowledge base. Students then break into research groups that focus on a specific topic related to the central topic. For example, a class studying food chains may break into five groups that each focus on a different aspect, such as photosynthesis or consumers. Students research their subtopic as a group, with individuals majoring by pursuing their own research agendas within the subtopic.
Students engage in regular crosstalk sessions, in which the different groups explain their work, ask and answer questions, and refine their understanding. The research activities include reciprocal teaching (Palincsar & Brown, 1984), guided writing and composing, consultation with experts outside the classroom, and cross-age tutoring. Finally, students from each of the subtopic groups come together to form a jigsaw group (Aronson, 1978) in order to share their learning and work together on a consequential task. The consequential tasks require students to share knowledge across groups and serve as occasions for exhibition and reflection.
Scaffolding. Scaffolding helps learners carry out tasks that are beyond their capabilities. Quintana et al. (2004) suggest twenty specific strategies for designing scaffolds to support understanding, inquiry, articulation, and reflection in computer-based environments. In most situations, scaffolding naturally fades as learners are able to accomplish tasks on their own.
Sandoval and Reiser (2004) have developed a computer system called the Biology Guided Inquiry Learning Environment (BGuILE) that supports students in making scientific arguments in the context of population genetics. The system presents the students with a mystery concerning why many of the finches in the Galapagos Islands died during a drought. In order to solve the mystery, students have to analyze extensive data that were collected by scientists and come up with a reasoned conclusion as to why some finches died while others survived. The Explanation Constructor tool in the system prompts the students to put in all the pieces of a sound genetics-based argument, after they have decided what caused the finches to die. Hence, the system scaffolds students to articulate their argument in a much more explicit form than they would normally do.
The concept of scaffolding comes from Vygotsky's 1978 concept of the zone of proximal development, which described how adults support learners to accomplish tasks that they cannot accomplish themselves. The focus of research on scaffolding has been on supporting individuals, but Kolodner et al. (2003) point out that it is important to scaffold groups as well. So for example, in teaching science, they provide students with focused collaboration activities to solve simple problems, which they call launcher units. Engaging in these activities and reflecting on them helps students to collaborate more effectively and to understand the value of collaboration.
Articulation. In order to abstract learning from particular contexts, it is important for learners to articulate their thinking and knowledge. For example, Lampert (Lampert, et al., 1996) showed how fifth grade children can form a community of inquiry about important mathematical concepts. She engaged students in discussion of their conjectures and interpretations of each other's reasoning. Techniques of this kind have been successful with even younger children (Cobb & Bauersfeld, 1995) and may underlie the success of Japanese mathematical education.
A notable method for fostering articulation in science is the Itakura method developed in Japan (Hatano & Inagaki, 1991). First, students make different predictions about what will happen in a simple experiment, where they are likely to have different expectations. For example, one experiment involves lowering a clay ball into water and predicting what will happen. After students make their initial predictions, they discuss and defend why they think their predictions are correct. After any revisions in their predictions, the experiment is performed and discussion ensues as to why the result came out the way it did.
The Knowledge Forum environment developed by Scardamalia and Bereiter (1994) is an environment in which students articulate their ideas in writing over a computer network. The model involves students investigating problems in different subject areas over a period of weeks or months. As students work, they enter their ideas and research findings as notes in an on-line knowledge base. The software scaffolds students in constructing their notes through features such as theory-building scaffolds (e.g. “My Theory,” “I Need to Understand”) or debate scaffolds (e.g. “Evidence For”). Students can read through the knowledge base, adding text, graphics, questions, links to other notes, and comments on each other's work. When someone has commented on their work, the system automatically notifies them about it. The emphasis is on progress toward collective goals of understanding, rather than individual learning and performance.
Reflection. Reflection encourages learners to look back on their task performance and compare it to other performances, such as their previous performances and those of experts. One of the most effective ways to improve performance is for learners to evaluate how they did with respect to a set of criteria that determine good performance. For example, White and Frederiksen (1998) showed that students who evaluated their performance on science projects using a set of eight criteria learned much more than students who carried out the same tasks, but did not reflect on their performance. In fact, this reflection helped the weaker students much more than the stronger students.
The essential way people get better at doing things is by thinking about what they are going to do beforehand, by trying to do what they have planned, and by reflecting back on how well what they did came out. If they can articulate criteria for evaluating what they did, this will help them as they plan what they do on the next cycle. The wide availability of computers and other recording technologies makes performances easier to produce and to reflect upon. For example, students can now produce their own news broadcasts, musical performances, or plays, on audiotape or videotape. Furthermore, they can play these back, reflect upon them, and edit them until they are polished.
As these examples illustrate, there has been extensive research in recent years that has incorporated the principles of cognitive apprenticeship in the design of learning environments. As computer-based learning environments become more pervasive, there is likely to be continued development of new ways to embody these principles in their design.
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