James W. Pellegrino
University of Illinois at Chicago
The past three decades have produced an extraordinary outpouring of scientific work on the processes of thinking and learning and on the development of competence. Much of this work has important implications for the design of learning environments and for the nature of instructional practices that maximize individual and group learning. Simultaneously, information technologies have advanced rapidly.
They now render it possible to design much more complex, sophisticated, and potentially more powerful learning and instructional environments. Although much is now possible given theoretical, empirical, and technological advances, many questions remain to be answered. What principles do we need to consider in connecting together learning theory, instructional practice, and information technologies? How can we do so in effective and powerful ways?
In this chapter consideration is given to how contemporary learning theory can be connected to instructional practice to build better learning environments. A special concern is how we can capitalize on some of the many capacities and potentials of information technologies. This chapter begins by considering general linkages among curriculum, instruction, and assessment. With that as a context it moves to a consideration of some of the principal findings from research on learning that have clear implications for instructional practice. This brings us back to a consideration of the implications of knowledge about how people learn for some general issues of curriculum, instruction, and assessment, which is then followed by a more detailed discussion of important principles for the design of powerful learning and instructional environments. In discussing those principles, mention is made of ways in which technology can support their realization.
THE CURRICULUM–INSTRUCTION–ASSESSMENT
TRIAD
Whether recognized or not, three things are central to the educational enterprise: curriculum, instruction, and assessment. The three elements of this triad are linked, although the nature of their linkages and reciprocal influence is often less explicit than it should be. Furthermore, the separate pairs of connections are often inconsistent, which can lead to an overall incoherence in educational systems.
Curriculum consists of the knowledge and skills in subject matter areas that teachers teach and students are supposed to learn. The curriculum generally consists of a scope or breadth of content in a given subject area and a sequence for learning. Standards, such as those developed in mathematics and science (National Council of Teachers of Mathematics [NCTM], 2000; National Research Council, 1996), typically outline the goals of learning, whereas curriculum sets forth the more specific means to be used to achieve those ends. Instruction refers to methods of teaching and the learning activities used to help students master the content and objectives specified by a curriculum and attain the standards that have been prescribed. Instruction encompasses the activities of both teachers and students. It can be carried out by a variety of methods, sequences of activities, and topic orders. Assessment is the means used to measure the outcomes of education and the achievement of students with regard to important knowledge and competencies. Assessment may include both formal methods, such as large-scale state assessments, or less formal classroom-based procedures, such as quizzes, class projects, and teacher questioning.
A precept of educational practice is the need for alignment among curriculum, instruction, and assessment (e.g., NCTM, 2000). Alignment, in this sense, means that the three functions are directed toward the same ends and reinforce each other rather than working at cross-purposes. Ideally, an assessment should measure what students are actually being taught, and what is actually being taught should parallel the curriculum one wants students to master. If any of the functions are not well synchronized, it will disrupt the balance and skew the educational process. Assessment results will be misleading, or instruction will be ineffective. Alignment is often difficult to achieve, however. Often what is lacking is a central theory about the nature of learning and knowing which guides the process and around which the three functions can be coordinated.
Decisions about curriculum, instruction, and assessment are further complicated by actions taken at different levels of the educational system, including the classroom, the school or district, and the state or nation. Each of these levels has different needs, and each uses assessment data in varied ways for somewhat different purposes. Each also plays a role in making decisions and setting policies for curriculum, instruction, and assessment, although the locus of power shifts depending on the type of decision involved. Some of these actions emanate from the top down, whereas others arise from the bottom up. Nations or states generally exert considerable influence over curriculum; classroom teachers have more latitude in instruction. Nations or states tend to determine policies on assessment for program evaluation; teachers have greater control over assessment for learning. This situation means that adjustments must continually be made among curriculum, instruction, and assessment not only horizontally, within the same level (such as within school districts), but also vertically across levels. For example, a change in national or state curriculum policy will require adjustments in assessment and instruction at all levels.
Most current approaches to curriculum, instruction, and assessment are based on theories and models that have not kept pace with contemporary knowledge of how people learn (Pellegrino, Chudowsky, & Glaser, 2001; Shepard, 2000). They have been designed on the basis of implicit and highly limited conceptions of learning. Those conceptions tend to be fragmented, outdated, and poorly delineated for domains of subject matter knowledge. Alignment among curriculum, instruction, and assessment could be better achieved if all three were derived from a scientifically credible and shared knowledge base about cognition and learning in the subject matter domains. 1 The model of learning would provide the central bonding principle, serving as a nucleus around which the three functions would revolve. Without such a central core, and under pressure to prepare students for high-stakes external accountability tests, teachers may feel compelled to move back and forth between instruction and external assessment and teach directly to the items on a high-stakes test. This approach can result in an undesirable narrowing of the curriculum and a limiting of learning outcomes. Such problems can be ameliorated if, instead, decisions about both instruction and assessment are guided by a model of learning in the domain that represents the best available scientific understanding of how people learn. This brings us to a consideration of what we actually know about the nature of learning and knowing.
IMPORTANT PRINCIPLES ABOUT LEARNING AND TEACHING
Two recent National Academy of Sciences reports on “How People Learn” (Bransford, Brown, & Cocking, 1999; Donovan, Bransford, & Pellegrino, 1999) provide a broad overview of research on learners and learning and on teachers and teaching. Although there are many important findings that bear on issues of learning and instruction, three of the findings described in those reports are highlighted in this chapter. Each has a solid research base to support it, has strong implications for how we teach, and helps us think about ways in which technology assists in the design and delivery of effective learning environments.
The first important principle about how people learn is that students come to the instructional setting with existing knowledge structures and schemas that include preconceptions about how the world works. If their initial understanding is not engaged, they may fail to grasp the new concepts, procedures, and information that are taught, or they may learn them for purposes of an exercise or test but revert to their preconceptions outside the learning or occupational setting. Those initial understandings can have a powerful effect on the integration of new concepts and information. Sometimes those understandings are accurate, providing a foundation for building new knowledge. But sometimes they are inaccurate. In science, students often have misconceptions of physical properties that cannot be easily observed (Carey & Gelman, 1991). In humanities, their preconceptions often include stereotypes or simplifications, as when history is understood as a struggle between “good guys” and “bad guys” (Gardner, 1991).
Drawing out and working with existing understandings is important for learners of all ages. Numerous research studies demonstrate the persistence of preexisting understandings even after a new model has been taught that contradicts the naive understanding (Vosniadou & Brewer, 1989). For example, students at a variety of ages persist in their beliefs that seasons are caused by the earth’s distance from the sun rather than by the tilt of the earth (Harvard–Smithsonian Center for Astrophysics, 1987). They believe that an object that has been tossed in the air has both the force of gravity and the force of the hand that tossed it acting on it, despite training to the contrary (Clement, 1982). For the scientific understanding to replace the naive understanding, students must reveal the latter and have the opportunity to see where it falls short.
The second important principle about how people learn is that to develop competence in an area of inquiry, students must (a) have a deep foundation of factual and procedural knowledge; (b) understand facts, procedures, and ideas in the context of a conceptual framework; and (c) organize knowledge in ways that facilitate retrieval and application. This principle emerges from research that compares the performance of experts and novices, and from research on learning and transfer. Experts, regardless of the field, always draw on a richly structured information base. They are not just “good thinkers” or “smart people.” The ability to plan a task, to notice patterns, to generate reasonable arguments and explanations, and to draw analogies to other problems are all more closely intertwined with factual and procedural knowledge than was once believed.
However, knowledge of a large set of disconnected facts or procedures is not sufficient. To develop competence in an area of inquiry, students must have opportunities to learn with understanding. Key to expertise is a deep understanding of the domain in which they are working that transforms factual and procedural information into “usable knowledge.” A pronounced difference between experts and novices is that experts’ command of concepts and procedures shapes their understanding of new information. It allows them to see patterns, relationships, or discrepancies that are not apparent to novices. They do not necessarily have better overall memories than other people. But their conceptual understanding allows them to extract a level of meaning from information that is not apparent to novices, and this helps them select, remember, and apply relevant information. Experts are also able to fluently access relevant knowledge because their understanding of subject matter allows them to quickly identify what is relevant. Hence, their working memory and attentional capacity is not over-taxed by complex events.
A key finding in the learning and transfer literature is that organizing information into a conceptual framework allows for greater “transfer.” It allows the student to apply what was learned in new situations and to learn related information more quickly (Holyoak, 1984; Novick & Holyoak, 1991). The student who has learned geographical information for the Americas in a conceptual framework approaches the task of learning the geography of another part of the globe with questions, ideas, and expectations that help guide acquisition of the new information. Understanding the geographical importance of the Mississippi River sets the stage for the student’s understanding of the geographical importance of the Rhine. And as concepts are reinforced, the student will transfer learning beyond the classroom, observing and inquiring about the geographic features of a visited city that help explain its location and size.
A third critical idea about how people learn is that a “metacognitive” approach to instruction can help students learn to take control of their own learning by defining learning goals and monitoring their progress in achieving them. In research with experts who were asked to verbalize their thinking as they worked, it has been revealed that they monitor their own understanding carefully. They make note of when additional information is required for understanding, whether new information is consistent with what they already know, and what analogies can be drawn that would advance their understanding. These metacognitive monitoring activities are an important component of what is called adaptive expertise (Hatano, 1990).
Because metacognition often takes the form of an internal conversation, it can easily be assumed that individuals will develop the internal dialogue on their own. Yet many of the strategies we use for thinking reflect cultural norms and methods of inquiry in a given domain of knowledge or work (Brice-Heath, 1981, 1983; Hutchins, 1995; Suina & Smolkin, 1994). Research has demonstrated that individuals can be taught these strategies, including the ability to predict outcomes, explain to oneself in order to improve understanding, and note failures to comprehend. They can learn to activate background knowledge, plan ahead, and apportion time and memory. However, the teaching of metacognitive activities must be incorporated into the subject matter and occupational skills that students are learning. These strategies are not generic across situations, and attempts to teach them as generic can lead to failure to transfer. Teaching metacognitive strategies in context has been shown to improve understanding and problem solving in physics (White & Frederiksen, 1998) and to facilitate heuristic methods for mathematical problem solving (Schoenfeld, 1983, 1984, 1991). And metacognitive practices have been shown to increase the degree to which students transfer to new settings and events (Palincsar & Brown, 1984; Scardamalia, Bereiter, & Steinbach, 1984; Schoenfeld, 1983, 1984, 1991).
The three core learning principles briefly described, simple though they may seem, have profound implications for teaching and for the potential of technology to assist in that process. First, teachers must draw out and work with the preexisting understandings that their students bring with them. The teacher must actively inquire into students’ thinking, creating classroom tasks and conditions under which student thinking can be revealed. Students’ initial conceptions then provide the foundation on which the more formal understanding of the instructional content is built. The roles for assessment must be expanded beyond the traditional concept of “testing.” The use of frequent formative assessment helps make students’ thinking visible to themselves, their peers, and their teacher. This provides feed-back that can guide modification and refinement in thinking. Given goals of learning with understanding, assessments must tap understanding rather than the mere ability to repeat facts or perform isolated skills.
Second, teachers must teach some subject matter in depth, providing many examples in which the same concept is at work and providing a firm foundation of factual and procedural knowledge. This requires that superficial coverage of all topics in a subject area must be replaced with in-depth coverage of fewer topics that allows key concepts and methods in that domain to be understood. The goal of coverage need not be abandoned entirely, of course. But there must be a sufficient number of cases of in-depth study to allow students to grasp the defining concepts in specific domains or areas of occupational skill.
Third, the teaching of metacognitive skills should be integrated into the curriculum in a variety of content areas. Because metacognition often takes the form of an internal dialogue, many students may be unaware of its importance unless the processes are explicitly emphasized by teachers. An emphasis on metacognition needs to accompany instruction in multiple areas of study because the type of monitoring required will vary. Integration of metacognitive instruction with discipline-based learning can enhance student achievement and develop in students the ability to learn independently.
University of Illinois at Chicago
The past three decades have produced an extraordinary outpouring of scientific work on the processes of thinking and learning and on the development of competence. Much of this work has important implications for the design of learning environments and for the nature of instructional practices that maximize individual and group learning. Simultaneously, information technologies have advanced rapidly.
They now render it possible to design much more complex, sophisticated, and potentially more powerful learning and instructional environments. Although much is now possible given theoretical, empirical, and technological advances, many questions remain to be answered. What principles do we need to consider in connecting together learning theory, instructional practice, and information technologies? How can we do so in effective and powerful ways?
In this chapter consideration is given to how contemporary learning theory can be connected to instructional practice to build better learning environments. A special concern is how we can capitalize on some of the many capacities and potentials of information technologies. This chapter begins by considering general linkages among curriculum, instruction, and assessment. With that as a context it moves to a consideration of some of the principal findings from research on learning that have clear implications for instructional practice. This brings us back to a consideration of the implications of knowledge about how people learn for some general issues of curriculum, instruction, and assessment, which is then followed by a more detailed discussion of important principles for the design of powerful learning and instructional environments. In discussing those principles, mention is made of ways in which technology can support their realization.
THE CURRICULUM–INSTRUCTION–ASSESSMENT
TRIAD
Whether recognized or not, three things are central to the educational enterprise: curriculum, instruction, and assessment. The three elements of this triad are linked, although the nature of their linkages and reciprocal influence is often less explicit than it should be. Furthermore, the separate pairs of connections are often inconsistent, which can lead to an overall incoherence in educational systems.
Curriculum consists of the knowledge and skills in subject matter areas that teachers teach and students are supposed to learn. The curriculum generally consists of a scope or breadth of content in a given subject area and a sequence for learning. Standards, such as those developed in mathematics and science (National Council of Teachers of Mathematics [NCTM], 2000; National Research Council, 1996), typically outline the goals of learning, whereas curriculum sets forth the more specific means to be used to achieve those ends. Instruction refers to methods of teaching and the learning activities used to help students master the content and objectives specified by a curriculum and attain the standards that have been prescribed. Instruction encompasses the activities of both teachers and students. It can be carried out by a variety of methods, sequences of activities, and topic orders. Assessment is the means used to measure the outcomes of education and the achievement of students with regard to important knowledge and competencies. Assessment may include both formal methods, such as large-scale state assessments, or less formal classroom-based procedures, such as quizzes, class projects, and teacher questioning.
A precept of educational practice is the need for alignment among curriculum, instruction, and assessment (e.g., NCTM, 2000). Alignment, in this sense, means that the three functions are directed toward the same ends and reinforce each other rather than working at cross-purposes. Ideally, an assessment should measure what students are actually being taught, and what is actually being taught should parallel the curriculum one wants students to master. If any of the functions are not well synchronized, it will disrupt the balance and skew the educational process. Assessment results will be misleading, or instruction will be ineffective. Alignment is often difficult to achieve, however. Often what is lacking is a central theory about the nature of learning and knowing which guides the process and around which the three functions can be coordinated.
Decisions about curriculum, instruction, and assessment are further complicated by actions taken at different levels of the educational system, including the classroom, the school or district, and the state or nation. Each of these levels has different needs, and each uses assessment data in varied ways for somewhat different purposes. Each also plays a role in making decisions and setting policies for curriculum, instruction, and assessment, although the locus of power shifts depending on the type of decision involved. Some of these actions emanate from the top down, whereas others arise from the bottom up. Nations or states generally exert considerable influence over curriculum; classroom teachers have more latitude in instruction. Nations or states tend to determine policies on assessment for program evaluation; teachers have greater control over assessment for learning. This situation means that adjustments must continually be made among curriculum, instruction, and assessment not only horizontally, within the same level (such as within school districts), but also vertically across levels. For example, a change in national or state curriculum policy will require adjustments in assessment and instruction at all levels.
Most current approaches to curriculum, instruction, and assessment are based on theories and models that have not kept pace with contemporary knowledge of how people learn (Pellegrino, Chudowsky, & Glaser, 2001; Shepard, 2000). They have been designed on the basis of implicit and highly limited conceptions of learning. Those conceptions tend to be fragmented, outdated, and poorly delineated for domains of subject matter knowledge. Alignment among curriculum, instruction, and assessment could be better achieved if all three were derived from a scientifically credible and shared knowledge base about cognition and learning in the subject matter domains. 1 The model of learning would provide the central bonding principle, serving as a nucleus around which the three functions would revolve. Without such a central core, and under pressure to prepare students for high-stakes external accountability tests, teachers may feel compelled to move back and forth between instruction and external assessment and teach directly to the items on a high-stakes test. This approach can result in an undesirable narrowing of the curriculum and a limiting of learning outcomes. Such problems can be ameliorated if, instead, decisions about both instruction and assessment are guided by a model of learning in the domain that represents the best available scientific understanding of how people learn. This brings us to a consideration of what we actually know about the nature of learning and knowing.
IMPORTANT PRINCIPLES ABOUT LEARNING AND TEACHING
Two recent National Academy of Sciences reports on “How People Learn” (Bransford, Brown, & Cocking, 1999; Donovan, Bransford, & Pellegrino, 1999) provide a broad overview of research on learners and learning and on teachers and teaching. Although there are many important findings that bear on issues of learning and instruction, three of the findings described in those reports are highlighted in this chapter. Each has a solid research base to support it, has strong implications for how we teach, and helps us think about ways in which technology assists in the design and delivery of effective learning environments.
The first important principle about how people learn is that students come to the instructional setting with existing knowledge structures and schemas that include preconceptions about how the world works. If their initial understanding is not engaged, they may fail to grasp the new concepts, procedures, and information that are taught, or they may learn them for purposes of an exercise or test but revert to their preconceptions outside the learning or occupational setting. Those initial understandings can have a powerful effect on the integration of new concepts and information. Sometimes those understandings are accurate, providing a foundation for building new knowledge. But sometimes they are inaccurate. In science, students often have misconceptions of physical properties that cannot be easily observed (Carey & Gelman, 1991). In humanities, their preconceptions often include stereotypes or simplifications, as when history is understood as a struggle between “good guys” and “bad guys” (Gardner, 1991).
Drawing out and working with existing understandings is important for learners of all ages. Numerous research studies demonstrate the persistence of preexisting understandings even after a new model has been taught that contradicts the naive understanding (Vosniadou & Brewer, 1989). For example, students at a variety of ages persist in their beliefs that seasons are caused by the earth’s distance from the sun rather than by the tilt of the earth (Harvard–Smithsonian Center for Astrophysics, 1987). They believe that an object that has been tossed in the air has both the force of gravity and the force of the hand that tossed it acting on it, despite training to the contrary (Clement, 1982). For the scientific understanding to replace the naive understanding, students must reveal the latter and have the opportunity to see where it falls short.
The second important principle about how people learn is that to develop competence in an area of inquiry, students must (a) have a deep foundation of factual and procedural knowledge; (b) understand facts, procedures, and ideas in the context of a conceptual framework; and (c) organize knowledge in ways that facilitate retrieval and application. This principle emerges from research that compares the performance of experts and novices, and from research on learning and transfer. Experts, regardless of the field, always draw on a richly structured information base. They are not just “good thinkers” or “smart people.” The ability to plan a task, to notice patterns, to generate reasonable arguments and explanations, and to draw analogies to other problems are all more closely intertwined with factual and procedural knowledge than was once believed.
However, knowledge of a large set of disconnected facts or procedures is not sufficient. To develop competence in an area of inquiry, students must have opportunities to learn with understanding. Key to expertise is a deep understanding of the domain in which they are working that transforms factual and procedural information into “usable knowledge.” A pronounced difference between experts and novices is that experts’ command of concepts and procedures shapes their understanding of new information. It allows them to see patterns, relationships, or discrepancies that are not apparent to novices. They do not necessarily have better overall memories than other people. But their conceptual understanding allows them to extract a level of meaning from information that is not apparent to novices, and this helps them select, remember, and apply relevant information. Experts are also able to fluently access relevant knowledge because their understanding of subject matter allows them to quickly identify what is relevant. Hence, their working memory and attentional capacity is not over-taxed by complex events.
A key finding in the learning and transfer literature is that organizing information into a conceptual framework allows for greater “transfer.” It allows the student to apply what was learned in new situations and to learn related information more quickly (Holyoak, 1984; Novick & Holyoak, 1991). The student who has learned geographical information for the Americas in a conceptual framework approaches the task of learning the geography of another part of the globe with questions, ideas, and expectations that help guide acquisition of the new information. Understanding the geographical importance of the Mississippi River sets the stage for the student’s understanding of the geographical importance of the Rhine. And as concepts are reinforced, the student will transfer learning beyond the classroom, observing and inquiring about the geographic features of a visited city that help explain its location and size.
A third critical idea about how people learn is that a “metacognitive” approach to instruction can help students learn to take control of their own learning by defining learning goals and monitoring their progress in achieving them. In research with experts who were asked to verbalize their thinking as they worked, it has been revealed that they monitor their own understanding carefully. They make note of when additional information is required for understanding, whether new information is consistent with what they already know, and what analogies can be drawn that would advance their understanding. These metacognitive monitoring activities are an important component of what is called adaptive expertise (Hatano, 1990).
Because metacognition often takes the form of an internal conversation, it can easily be assumed that individuals will develop the internal dialogue on their own. Yet many of the strategies we use for thinking reflect cultural norms and methods of inquiry in a given domain of knowledge or work (Brice-Heath, 1981, 1983; Hutchins, 1995; Suina & Smolkin, 1994). Research has demonstrated that individuals can be taught these strategies, including the ability to predict outcomes, explain to oneself in order to improve understanding, and note failures to comprehend. They can learn to activate background knowledge, plan ahead, and apportion time and memory. However, the teaching of metacognitive activities must be incorporated into the subject matter and occupational skills that students are learning. These strategies are not generic across situations, and attempts to teach them as generic can lead to failure to transfer. Teaching metacognitive strategies in context has been shown to improve understanding and problem solving in physics (White & Frederiksen, 1998) and to facilitate heuristic methods for mathematical problem solving (Schoenfeld, 1983, 1984, 1991). And metacognitive practices have been shown to increase the degree to which students transfer to new settings and events (Palincsar & Brown, 1984; Scardamalia, Bereiter, & Steinbach, 1984; Schoenfeld, 1983, 1984, 1991).
The three core learning principles briefly described, simple though they may seem, have profound implications for teaching and for the potential of technology to assist in that process. First, teachers must draw out and work with the preexisting understandings that their students bring with them. The teacher must actively inquire into students’ thinking, creating classroom tasks and conditions under which student thinking can be revealed. Students’ initial conceptions then provide the foundation on which the more formal understanding of the instructional content is built. The roles for assessment must be expanded beyond the traditional concept of “testing.” The use of frequent formative assessment helps make students’ thinking visible to themselves, their peers, and their teacher. This provides feed-back that can guide modification and refinement in thinking. Given goals of learning with understanding, assessments must tap understanding rather than the mere ability to repeat facts or perform isolated skills.
Second, teachers must teach some subject matter in depth, providing many examples in which the same concept is at work and providing a firm foundation of factual and procedural knowledge. This requires that superficial coverage of all topics in a subject area must be replaced with in-depth coverage of fewer topics that allows key concepts and methods in that domain to be understood. The goal of coverage need not be abandoned entirely, of course. But there must be a sufficient number of cases of in-depth study to allow students to grasp the defining concepts in specific domains or areas of occupational skill.
Third, the teaching of metacognitive skills should be integrated into the curriculum in a variety of content areas. Because metacognition often takes the form of an internal dialogue, many students may be unaware of its importance unless the processes are explicitly emphasized by teachers. An emphasis on metacognition needs to accompany instruction in multiple areas of study because the type of monitoring required will vary. Integration of metacognitive instruction with discipline-based learning can enhance student achievement and develop in students the ability to learn independently.
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