This entry contains the following:
- CASE-BASED LEARNING
- DISCOVERY LEARNING
- INQUIRY-BASED LEARNING
- PROBLEM-BASED LEARNING
- PROJECT-BASED LEARNING
The term constructivism has played a dominant role in educational literature for a number of decades. While educators generally agree on several core aspects of constructivism, significantly different interpretations, perspectives, and approaches exist regarding the details of constructivist learning and teaching. This section discusses (a) the historical roots of constructivism, (b) perspectives on constructivism as epistemological theory, learning theory, and pedagogy; (c) the continuum of constructivist perspectives from individual to social, (d) evidence for the efficacy and adoption of constructivism, (e) the key assumptions about constructivist learning and instruction, and (f) introductions to several instructional approaches involving constructivist designs.
HISTORICAL ROOTS OF CONSTRUCTIVISM
Constructivism, although relatively new in its current form, has deep historical roots. At their core, constructi-vist perspectives focus on how learners construct their own understanding. Some philosophers, such as Socrates, focused on helping students construct meanings on their own rather than having authority figures transmit information to them. Immanuel Kant (1724–1804) built upon this by recognizing that the way learners perceive stimuli from their environment shapes their understanding of the world. In the early 20th century, John Dewey (1859– 1952) proposed that education should work with students' current understanding, taking into account their prior ideas and interests. Later, Jean Piaget (1896–1980) defined accommodation and assimilation as ways for new knowledge to build upon previous knowledge. The ideas of Lev Vygotsky (1896–1934) also influenced constructivism. He helped increase awareness of the interactions between the individual, interpersonal, and cultural historical factors that affect learning.
CONSTRUCTIVISM AS EPISTEMOLOGICAL THEORY, LEARNING THEORY, AND PEDAGOGY
The term constructivism can refer to one of many different but related concepts. More specifically, constructivist perspectives can focus on epistemological theory, learning theory, and pedagogy.
As an epistemological theory, constructivism focuses on how bodies of knowledge come to be. This perspective is important to note even though this view of constructivism is not discussed in the educational literature as frequently as other views. Constructivism as an epis-temological theory holds that disciplines, such as history and mathematics, are constructed by human interactions Page 263 | Top of Articleand decisions. For some disciplines, such as literature, this idea is fairly well accepted; there are certain books that most people agree are worth reading and others that are purposefully forgotten. For disciplines such as science and mathematics, however, the idea that people (and not nature) construct the bounds of the disciplines and the concepts within them remains contentious.
More commonly, educators view constructivism as a learning theory. Some educators use the term constructi-vist simply to indicate a non-behaviorist learning theory. While constructivist learning theories are non-behaviorist, constructivism involves much more than simple opposition to a previous learning theory. From the perspective of constructivism, learners construct knowledge based on what they already understand as they make connections between new information and old information. Students' prior ideas, experiences, and knowledge interact with new experiences and their interpretations of the environment around them. Research by Savery & Duffy (1995) suggests that learning how to use constructivist theories involves many interactions between the content, the context, the activity of the learner, and the goals of the learner.
Cognitive conflict drives this knowledge-building process. Cognitive conflict occurs for learners when they encounter and recognize discrepancies between what they already know and new persuasive information that brings their current understanding into question. These discrepancies cause cognitive tension requiring adjustment to reduce the discrepancies. When students resolve these discrepancies they actively figure out ways to reconcile their prior knowledge or understanding with the new information. Students may construct new knowledge from pieces of prior knowledge or restructure prior knowledge. Thus the resolution of cognitive conflict drives learning.
Finally, based on the core ideas of constructivist learning theory, constructivist pedagogy proposes that instruction must take students' prior ideas, experiences, and knowledge into account while providing opportunities for students to construct new understanding. Con-structivist pedagogies are discussed in greater detail below, in the sections titled Assumptions about Constructivist Learning and Instruction, and Instructional approaches with constructivist designs.
CONSTRUCTIVIST PERSPECTIVES FROM INDIVIDUAL TO SOCIAL
While the general principles discussed above apply to most constructivist theories and pedagogies, significantly different interpretations have evolved regarding the details. One key distinction, discussed by Phillips (2000) and other educators, among constructivist perspectives involves the continuum of interpretations in terms of where the construction of knowledge takes place. Radical constructivism anchors one end of this continuum and social constructivism anchors the other. Most educators' theoretical commitments fall somewhere between these two perspectives.
Radical constructivism proposes that the construction of knowledge takes place solely in the learner's mind and on an individual level. Ernst von Glasersfeld (1917–) refined many of the core ideas of radical constructivism. McCarty and Schwandt (2000) explain that according to radical constructivism, concepts form through the learner's experiences with objects or events as the learner notes similarities and differences among the experiences and gradually builds up a concept relating to that object or event.
Radical constructivism is similar in many ways to Jean Piaget's perspectives on assimilation and accommodation and to theories of information processing. Both Piagetian and information processing theories view learning as a cognitive activity through which individuals actively incorporate new information and experiences into the information and understandings already stored in memory. Piaget explains these processes in terms of assimilation, in which learners add new information into their existing knowledge frameworks, and accommodation, in which the new information causes cognitive conflict that results in the reorganization of learners' knowledge frameworks. Information processing theory uses a computer metaphor to explain how knowledge construction works. The learner perceives various stimuli, encodes them into useful information, and then stores the information for later use. The learner is able to modify previous knowledge or strategies in order to help with current problem solving and develop more sophisticated knowledge. In alignment with radical constructi-vist perspectives, therefore, both perspectives focus on how the individual processes and relates new information to information already in the mind.
Radical constructivism holds serious implications for learning and teaching. Most importantly, from the perspective of radical constructivism, a person cannot ascertain that what other people have constructed in their minds is exactly the same as what he or she has constructed. In spite of this paradox, teachers must act “as if there were a world about which meanings were shared” (Howe & Berv, 2000, p. 33).
Social constructivism represents the other end of the continuum. Social constructivism, heavily influenced by Vygotsky and sociocultural theory, proposes that learning takes place in the interaction between people and their
environment. An extreme social constructivist view developed by Kenneth Gergen proposes no strict boundary between the mind and the environment or between language and reality. This view further proposes that a person's understanding of the world cannot be removed from the way he or she uses language to describe it, view it, and discuss it with others.
Less extreme social constructivist perspectives propose simply that students construct knowledge through an interaction with their surroundings rather than in isolation from them. Social interactions play an important part in knowledge construction because they support the introduction and resolution for the cognitive conflict at the heart of constructivist learning perspectives. Although moderate social perspectives acknowledge the role of people's prior knowledge in the evolution of their understanding, moderate perspectives propose that knowledge structures evolve socially through observation and interaction with other people and the environment. Sociocultural theories and perspectives emphasize the importance of learners' interactions with their social environment in order to determine what should be learned and how it should be learned. Also, being able to discuss developing ideas with others helps learners determine how to modify their ideas.
Different flavors of social constructivism have different emphases for learning and instruction. Some emphasize cognitive skills and strategies for learning while others emphasize the big ideas or concepts in a discipline. Some social constructivists propose three fundamental commitments for teaching and learning: treat the discipline with respect, treat students' ideas with respect, and view the discipline as a “collective intellectual endeavor situated within a community” (Ball & Bass, 2000, p. 197). From this perspective, instruction should involve a democratic process in which students and the teacher discuss what represents publicly shared knowledge and what does not. Instruction should focus on this publicly shared knowledge in order to allow all the students to build upon what they know and to help the teacher understand what steps need to be taken in order to achieve certain goals.
EFFICACY AND ADOPTION OF CONSTRUCTIVISM
Constructivist teaching, introduced by Piaget in the early 1930s, has found increasingly wide acceptance by researchers and educators since the early 1980s. Although widely accepted, however, constructivism remains less widely practiced. A study by Moussiaux and Norman (1997) involving 49 schools and 289 teachers in Michigan found that only 28% to 50% of teachers claimed to use constructivist methods. Furthermore, as noted by Jones and Carter (2007), many teachers who believe they enact constructivist methods do not actually use methods in alignment with constructivist theories. Teachers should be aware of not just the instructional strategies they are implementing but also the theoretical reasons behind those strategies and how they can be used in different ways. Abbott and Fouts found that only 17% of 669 classrooms in 34 schools in Washington actually incorporated constructivism into instruction.
Barron and colleagues (1998) suggest that construc-tivist approaches remain underimplemented and underutilized because constructivist teaching practices are foreign to students and teachers, and difficult to apply. Many people in the general public remain suspicious when teaching methods differ from the forms of instruction they experienced in school. High-stakes testing represents Page 265 | Top of Articleanother obstacle to wider implementation of constructi-vist instruction. Although state education standards usually include constructivist goals, these standards and goals often do not align with the high-stakes tests or the preparation for those tests. A review by Jones and Carter (2007) suggested that wider implementation of construc-tivist approaches will require changes in teacher attitudes and beliefs in addition to educational reform.
While authentic constructivist pedagogies remain relatively uncommon in classrooms, many studies support the potential efficacy of constructivist approaches. Abbot and Fouts (2003), for example, found a significant correlation between constructivist teaching and higher achievement. Different constructivist approaches appear, however, to vary in their levels of efficacy. Research on guided discovery learning and pure discovery learning demonstrates that students engaging in guided discovery learning activities outperform students in pure discovery curricula (Shulman & Keisler (1966), Kittel (1957), and Mayer (2004)). In summary, studies have shown that constructivist approaches have great potential but require authentic implementation in order to achieve that potential.
ASSUMPTIONS ABOUT CONSTRUCTIVIST LEARNING AND INSTRUCTION
Although constructivist instruction can take many forms based on the instructor's theoretical commitments, con-structivist teaching at its core focuses on students' active role in their own learning as they build and organize their knowledge. Constructivist instructional frameworks, such as those discussed by Lebow (1993), often focus on the following attributes: personal relevance, the opportunity to generate new knowledge, personal autonomy, active engagement, collaboration, the opportunity to reflect on learning, and pluralism. In addition, Langer and Apple-bee (1987) discuss how the core goals of constructivist teaching often include promoting democratic learning environments and student-centered instruction. As a result, “teachers are apt to feel comfortable in this role only if they view uncertainty and conflict as natural and potentially growth producing for members of the learning community” (Prawat & Floden, 1994, p. 40).
To create personal relevance, learners need to understand the benefits and importance of the curriculum for their own interests. Teachers can promote this relevance by incorporating real-life situations and experiences into their students' classroom learning. To give students an opportunity to be involved in creating knowledge, the learner should be involved not in activities in which the goal is to memorize facts but in problem-solving activities. For instructional design geared toward radical constructivism, students should be provided with personal autonomy in which individual work is part of the instructional framework. Also, students should be part of the process of designing the problem as well as dictating the process for working on that problem. Furthermore, to actively engage students, “the teacher's role should be to challenge the learner's thinking—not to dictate or attempt to proceduralize that thinking” (Savery & Duffy, 2001, p. 5). For instruction geared toward social constructivism, collaboration provides opportunities for students to interact and teach one another in small group work.
INSTRUCTIONAL APPROACHES WITH CONSTRUCTIVIST DESIGNS
While many pedagogical approaches integrate key con-structivist assumptions about learning and instruction discussed above, five approaches currently receive significant attention. These include (a) case-based learning, (b) discovery learning, (c) inquiry-based learning, (d) problem-based learning, and (e) project-based learning.
Case-based learning, as Herreid (1997) explains, uses real-life examples to build knowledge by resolving questions about a specific case. Usually these questions have no single right answer. Generally, case-based learning focuses on small groups and the interactions between the participants. The teacher facilitates the students' interactions while the students choose analysis techniques and work toward solutions of the open-ended problem. Under this pedagogical approach, students learn content while exposed to real-life issues. Students benefit from this type of instruction because they are given an opportunity for decision making as part of their learning process and because they experience and address different viewpoints.
Discovery learning engages learners in problem solving to make a discovery, as described by Mayer (2004). According to Seymour Papert, “The role of the teacher is to create the conditions for invention rather than provide ready-made knowledge” (Papert, 1980). The instructional design of discovery learning provides students with a problem and the opportunity for exploration to formulate solutions to the problem. The teacher guides the development of problem-solving skills and the creativity of the students. Discovery learning works on the assumption that students are more likely to retain knowledge if they discover it on their own. Students benefit from this type of instruction because it fosters curiosity and creativity.
As discussed by Edelson, Gordin, and Pea (1999), inquiry-based learning places the responsibility for learning and understanding concepts on the student. In other words, inquiry learning requires students to determine the content, the learning process, and the assessment of Page 266 | Top of Articlelearning. Inquiry-based methods use questions to guide instruction rather than predetermined topics. Usually this instructional design begins with a general theme that serves as a starting point for learning. Then the instruction builds upon the responses and interactions of the students. Teachers monitor the students' learning process through interviews, journaling, and group discussions. Students benefit from this instructional approach because they develop meta-cognitive learning skills and research skills upon which they can build toward future educational experiences.
Similar to case-based learning, problem-based learning teaches students to think critically, analyze problems, and use appropriate resources to solve real-life problems. Through this process, students identify the nature of the problem and determine what resources they need to utilize to solve the problem, as described by Boud & Feletti (1997). The teacher offers scaffolding by providing examples of how to approach the problem. A study by Wood (1993) suggests that students benefit as they integrate analytical skills with content knowledge as a member of a team.
Project-based learning also harnesses the process of investigation to encourage understanding. This method, as described by Polman (2000), engages students in a long-term project based on a real-life problem. These activities typically involve a wide range of interdisciplinary skills, including math, language, art, geography, science, and technology. This instructional design has less structure than traditional instruction because the students organize their own work. Generally, this approach involves collaborative learning. The teacher provides guidelines (such as checklists) for the students as they progress toward the completion of their project. By providing students with an authentic problem, project-based learning offers students a meaningful experience that promotes the development of research skills.
Abbott, M. L., & Fouts, J. T. (2003). Constructivist teaching and student achievement: The results of a school-level classroom observation study in Washington. Technical Report #5. Lynnwood, WA: Washington School Research Center.
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Elby, A. (2000). What students' learning of representations tells us about constructivism. Journal of Mathematical Behavior 19(4), 481–502.
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Jones, G., & Carter, G. (2007). Science teacher attitudes and beliefs. In S. K. Abell & N. G. Lederman (Eds.), Handbook of research on science education (pp. 1067–1104). Mahwah, NJ: Erlbaum.
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86.
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Langer, J., & Applebee, A. N. (1987). How writing shapes thinking: A study of teaching and learning. Urbana, IL: National Council of Teachers of English.
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Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books.
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Polman, J. L. (2000). Designing project-based science: Connecting learners through guided inquiry. New York: Teachers College Press.
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Cynthia M. D'Angelo
Douglas B. Clark
Case-based instructional methods are used in a variety of disciplines, including medicine, law, business, and education. Cases provide analogs of personal experience; they include a representation of a situation, how the situation was dealt with, and what the consequences were of dealing with it in that way (Kolodner, 1997). Cases describe an interesting story that will generate alternative perspectives from learners. Cases should provoke alternative ideas and require decision making (Herreid, 2008). There are a variety of methods for using cases in the context of instruction. Collaborative discussions among students about the case are common. Students are expected to bring their knowledge and perspectives to the consideration of the case, engage in argumentation about the interpretation of the case with their peers, and deepen their understanding of the issues at hand. In doing so, students use their prior experiences and knowledge to construct new knowledge and understandings.
The various disciplines that use cases as part of their instruction vary in how they define cases. It is difficult to distinguish a case from an example or a problem. Cases are used in various disciplines for different functions. In law schools, students study cases from the past and learn to use them as examples of judicial reasoning (Herreid, 2008). In medicine, cases are examples of previous medical decision making. In both law and medicine, the consequences of the particular decisions made are clear. In education, cases are used in preservice teacher education to illustrate theoretical ideas or to practice decision making. However, the consequences of one set of actions rather than another are much less clear in education than in other domains.
The use of cases in teacher education has the potential to bridge the gap between the declarative knowledge acquired in coursework and the procedural and conditional knowledge developed through practice. Many of the writings available about cases appeal to this potential (e.g., Doyle, 1990; Shulman, 1992). Because cases (e.g., a particular problem in a teacher's class) have face validity as representations of classrooms, teaching by using cases is often touted as a preferred teaching method (Silver-man, Welty, & Clark, 1996). However, in 1996 K. K. Merseth noted: “the collective voice of its proponents [the use of cases] far outweighs the power of existing empirical work” (p. 722).
The use of cases for instruction also has the potential to provide a window on developing expertise. More and less experienced individuals can be expected to respond to cases in different ways, providing instructors with insight into how cases are understood. There is some evidence that the use of cases can result in the development of theoretical and practical knowledge (Lundeberg, Levin, & Harrington, 1999). Case discussions can promote reflection and metacognition (Harrington, 1995; Levin, 1995). Much of the research on the use of cases in teacher education has been conducted within the context of college classrooms, and the designs of such research are typically pre- and posttest designs within specific courses that show an increase in the number and kind of theoretical constructs included in the posttest case analysis. Although this kind of research has yielded useful and important information, it is unclear whether the effects are due to the case method per se or simply to the exposure to the content of the course. Lundeberg and colleagues (1999) and Levin (1995) call for more systematic research on the use of cases in teacher education.
Students vary in their responses to case-based instruction. In a small study of nine veterinary students, students who had high levels of self-regulatory skills perceived the format of the instruction to be relevant and effective, whereas those students with low self-regulatory skills did not (Ertmer, Newman, & MacDougall, 1996). The degree to which participants engage in discussions related to a case also influences the quality of their thinking about the case (Levin, 1995).
The research on the use of cases has not been programmatic nor are the results systematically organized. It is difficult to draw conclusions about the effectiveness of case-based instruction and learning when there are different criteria across disciplines for what constitutes a good case, how effectiveness is assessed, and how research is conceptualized.
Doyle, W. (1990). Case methods in the education of teachers. Teacher Education Quarterly, 17, 7–16.
Ertmer, P., Newby, T., & MacDougall, M. (1996). Students' responses and approaches to case-based instruction: The role of reflective self-regulation. American Educational Research Journal, 33, 719–752.
Harrington, H. L. (1995). Fostering reasoned decisions: Case-based pedagogy and the professional development of teachers. Teaching and Teacher Education, 11, 203–214.
Herreid, C. F. (2008). What makes a good case? Some basic rules of good storytelling help teachers generate student excitement in the classroom. Retrieved April 17, 2008, from http://ublib.buffalo.edu/libraries/projects/cases/teaching/good-case.html .
Kolodner, J. L. (1997). Educational implications of analogy: A view from case-based reasoning. American Psychologist, 52, 57–66.
Levin, B. (1995). Using the case method in teacher education: The role of discussion and experience in teachers' thinking about cases. Journal of Teaching and Teacher Education, 11, 63–79.
Lundeberg, M. A., Levin, B. B., & Harrington, H. L. (1999). Who learns from cases and how: The research base for teaching and learning with cases. Mahwah, NJ: Erlbaum.
Merseth, K. K. (1996). Cases and case methods in teacher education. In J. Sikula (Ed)., Handbook of research on teacher education (2nd ed., pp. 722–744). New York: MacMillan.
Silverman, R., Welty, W. M., & Clark, S. (1996). From teaching incident to case. Innovative Higher Education, 2, 23–37.
Shulman, J. H. (Ed.). (1992). Case methods in teacher education. New York: Teachers College Press.
Angela M. O'Donnell
Discovery learning is an instructional method in which students are free to work in a learning environment with little or no guidance. For example, discovery learning is the method of instruction when students are given a math problem and asked to come up with a solution on their own, when students are given a scientific problem and allowed to conduct experiments, or when students are allowed to learn how a computer program works by typing commands and seeing what happens on a computer screen. The early 21st-century interest in discovery learning has its roots in Jerome Bruner's (1961) eloquent call for discovery methods of instruction and is echoed in Seymour Papert's (1980) focus on discovery methods for teaching computer programming and Deanna Kuhn's (2005) focus on discovery methods for teaching scientific thinking.
Constructivism is a theory of learning in which learners build knowledge in their working memory by engaging in appropriate cognitive processing of mental representations during learning. Richard Mayer (2008) identified three major cognitive processes in this view of learning as knowledge construction: (a) selecting, attending to relevant information that enters the cognitive system through the eyes and ears, (b) organizing, mentally arranging the selected material into coherent cognitive structures, and (c) integrating, mentally integrating the incoming material with prior knowledge activated from long-term memory. The role of active cognitive processing during learning has its roots in the construc-tivist theories of Frederick Bartlett (1932) and Jean Piaget (1970).
THE RELATIONSHIP BETWEEN CONSTRUCTIVISM AND DISCOVERY
What is the relation between constructivism as a theory of learning and discovery learning as a method of instruction? In a review of research in the learning sciences, John Bransford, Ann Brown, and Rodney Cocking (1999) showed how constructivism has become the dominant view of how people learn. Importantly, they noted that “the revolution in the study of the mind that has occurred in the last three or four decades has important implications for education” (Bransford, Brown, & Cocking, 1999, p. 3). Richard Mayer (2004) has shown how it might be tempting for educators to equate a constructi-vist vision of active learning (i.e., the idea that deep learning occurs when learners engage in active cognitive processing during learning) with a seemingly corresponding vision of active methods of instruction (i.e., instructional methods emphasizing learning by doing such as discovery learning). Mayer (2004, p. 15) refers to this confusion as the constructivist teaching fallacy, namely the idea that active learning requires active teaching. Instead, the goal of constructivist-inspired teaching methods is to prime appropriate cognitive activity during learning—a goal that does not necessarily require behavioral activity during learning. In short, Mayer (2004, p. 17) argues that “the formula constructivism = hands-on activity is a formula for educational disaster.”
In educational research, it is customary to compare the effects of pure discovery methods (in which learners receive little or no guidance while working on an educational task), guided discovery methods (in which learners receive substantial guidance while working on an educational task), and direct instruction (in which learners are presented with the to-be-learned material). The overwhelming pattern of results shows that pure discovery methods result in poorer learning than guided discovery or direct instruction. In their landmark book, Learning by Discovery: A Critical Appraisal, Lee Shulman and Evan Keiser concluded that research conducted during the 1960s did not favor pure discovery as an effective method of instruction: “there is no evidence that supports the
proposition that having students encounter a series of examples … and then having them induce the rule is superior to teaching the rule first and asking students to apply it” (1966, p. 191). More than 30 years later, John Sweller came to the same conclusion in comparing learning to solve math problems via worked examples versus via learning by doing: “worked examples proved superior to solving equivalent problems” (1999, p. ix).
In a review of research on teaching children how to solve Piagetian conservation tasks conducted mainly in the 1970s, C. J. Brainerd (2003) reported that children learned better when given heavy amounts of specific guidance than when left to learn on their own through hands-on discovery. In Teaching and Learning Computer Programming, edited by Richard Mayer (1988), researchers working in the 1980s reported that students learned the LOGO programming language better through guided discovery or direct instruction than through pure discovery. Subsequently, Klahr and Nigam (2004) found that students who learned to test scientific hypotheses by being given guidance on how to carry out controlled comparisons learned to reason scientifically better than students who learned through using hands-on pure discovery.
In their provocative review, “Why Minimal Guidance During Instruction Does Not Work,” Paul Kirschner, John Sweller, and Richard Clark (2006, p. 75) concluded: “although unguided or minimally guided instructional approaches are very popular and intuitively appealing … these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past century that consistently indicate that minimally guided instruction is Page 270 | Top of Articleless effective than instructional approaches that place a strong emphasis on guidance of the student learning process.” Similarly, in “Should There Be a Three-Strikes Rule against Pure Discovery Learning?” Richard Mayer demonstrated that “there is sufficient research evidence to make any reasonable person skeptical about the benefits of discovery learning—practiced under the guise of … constructivism—as a preferred instructional method” (2004, p. 14). Overall, in the educational research conducted between 1965 and 2005 across many different learning tasks, discovery methods (i.e., methods of instruction that emphasize hands-on activity without adequate guidance) have consistently been shown to be less effective than more guided methods of instruction.
Theories of learning in the early 2000s provide the theoretical rationale for providing guidance during learning. Based on John Sweller's (1999) cognitive load, Richard Mayer (2001) notes that discovery methods of instruction can encourage learners to engage in extraneous cognitive processing—cognitive processing that does not support the instructional goal. Because cognitive resources are limited, when a learner wastes precious cognitive capacity on extraneous processing, the learner has less capacity to support essential cognitive processing—to mentally represent the target material—and generative cognitive processing—to mentally organize and integrate the material. Guidance—in the form of scaffolding, coaching, modeling, or providing direct instruction—is effective when it helps guide the learner's essential and generative processing during learning while minimizing extraneous processing. In short, discovery learning is particularly ineffective when students do not naturally engage in appropriate cognitive processing during learning—a situation that characterizes most novice learners.
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Richard E. Mayer
Research in education and psychology that addresses the development of reasoning typically acknowledges the difficulty children (and adults) have in mastering this form of thinking. Constructivist teaching practice, particularly inquiry-based learning, seeks to mediate the learning process and make this kind of cognition an object of classroom instruction. Through inquiry learning, students play the role of scientists, a role that is familiar to researchers, as it is modeled on the authentic inquiry activities of professional scientists. Their tasks include formulating questions, designing informative investigations, analyzing patterns, drawing inferences, accessing evidence in responding to questions, formulating explanations from evidence, connecting explanations to knowledge, and communicating and justifying claims and explanations. The focus on inquiry learning originated with the work of Jean Piaget (1896–1980) on the development of adolescent reasoning skills, particularly his focus on the discontinuous, or abrupt, transition from concrete to formal operational thought during adolescence.
Piaget advanced an image of children at the early stages of development as intuitive scientists, actively engaged in understanding their environment and forming theories that they seek to support with evidence from their experience. The construction of these theories is driven by their exercise in informal experimentation, although this is not necessarily how people commonly understand experimentation in the work of professional scientists. Frequently, children's theories are hampered by bias, specifically toward confirmation of their existing theories and flawed efforts to integrate new information Page 271 | Top of Articlewith existing knowledge, a limitation one would not characterize as typical of scientific reasoning. Although Piaget focused on the development of children's understanding, he emphasized that their strategies of knowledge acquisition exhibit developmental trajectories as well. Research since Piaget has demonstrated that the developmental path he envisioned as discrete stages is more continuous in nature. Abandoning inefficient strategies of knowledge acquisition actually overlaps with adoption of more efficient strategies. One of the primary difficulties students have in evaluating evidence is understanding that their theories exist and can (and most of the time should) be revised by new information. Without some form of intervention to support this development, many students will not achieve this sophisticated level of thinking, and their adult thinking will continue to be characterized by inconsistent, inefficient strategy use.
USE OF INQUIRY-BASED LEARNING
Inquiry-based learning has come to be most frequently used in and associated with science instruction. Preeminent science educators in the United States identify inquiry as the preferred and prescribed method of teaching science. In fact, the first science teaching standard developed by the National Research Council requires science teachers to plan an inquiry-based science program for their students. The National Science Teachers Association (NSTA) has adopted these standards and proclaims itself an integral part of their dissemination and implementation. Typically, the procedure they advocate includes five distinct phases that reflect the scientific process:
Phase 1: engagement with a scientific question, event, or phenomenon connected with their current knowledge, though at odds with their own ideas, which motivates them to learn more;
Phase 2: exploration of ideas through hands-on experiences, formulating and testing hypotheses, problem-solving, and explaining observations;
Phase 3: analysis and interpretation of data, idea synthesis, model building, and clarification of concepts and explanations with scientific knowledge sources (including teachers);
Phase 4: extension of new understanding and abilities and application of learning to new situations (transfer);
Phase 5: review and assessment of what they have learned and how they have learned it (metacognition).
Although receiving most attention in science, inquiry skills have been cited as integral to virtually all subjects taught in K-12 schools. Professional organizations governing instruction in most subjects, from language arts to social studies to music education, include these skills in standards for their disciplines. According to these standards, then, students in K-12 schools can and should be expected to master the skills of inquiry in all areas.
PRINCIPLES OF INQUIRY-BASED LEARNING
The most common components of comprehensive approaches to inquiry-based learning are characterized by close adherence to authentic scientific inquiry as modeled by researchers and scientists themselves. Inquiry-based learning can take multiple forms depending on the task at hand: open, guided, coupled, or structured inquiry. The goals of each approach are dependent upon whether the learning objective involves conceptual or procedural knowledge or some combination of the two. Whether engaging in open or structured inquiry, students may perform most, if not all, components of reasoning, including generating hypotheses, designing experiments, gathering and evaluating evidence, and drawing conclusions based on evidence. The tasks they complete may involve investigation of an actual physical system or of a computer simulated system, an increasingly common practice given its cost-effectiveness and the ubiquitous availability of classroom technological tools. Relations between variables in these systems typically include some that reflect a student's prior beliefs and some that do not. Performance measures in these tasks can be numerous, ideally addressing all components of the process and in multiple forms with feedback to further inform student learning.
Most empirical studies of scientific investigation show significant age differences in performance, with adults typically outperforming children. Researchers have suggested that the development of metacognitive reasoning accounts for these weaknesses, specifically with regard to understanding false beliefs, growing awareness of the sources of personal knowledge, and differentiating and coordinating theory and evidence. The effective use of inquiry requires meta-level understanding of why a particular strategy works, suggesting that the goal of reasoning instruction in general, and inquiry learning methods in particular, should take particular account of metacognition.
EVIDENCE SUPPORTING THE USE OF INQUIRY-BASED LEARNING
Though not the only method of instruction, inquiry-based learning remains a clearly effective method for teaching the skills of inquiry and ensuring their long-term retention and transfer to new domains. Other instructional methods are appropriate complements to inquiry-based learning, particularly when the goals of Page 272 | Top of Articleinstruction are conceptual rather than procedural. There is a great deal more to learn in inquiry than just the control of variables strategy that has been the focus of research. Most research on scientific thinking, in fact, has been strictly focused on the control of variables strategy without consideration of the more complex metacognitive awareness required for its consistently successful use. This lack of concern with the meta-level of understanding has resulted in exclusive emphasis on the performance level, i.e., strategy execution. More critically, students must develop explicit models of inquiry procedures that include not just the reasoning process itself but also its value in acquiring knowledge.
Kuhn, D. (2006) Education for thinking. Cambridge, MA: Harvard University Press.
Inquiry and the national science education standards: A guide for teaching and learning. (2000). Washington, DC: NRC, National Academy Press.
Lehrer, R., & Schauble, L. (2006). Cultivating model-based reasoning in science education. In K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 371–388). New York: Cambridge University Press.
Zimmerman, C. (2007). The development of scientific thinking skills in elementary and middle school. Developmental Review, 27, 172–223.
David Dean, Jr.
Problem-based Learning (PBL) is an approach to instruction that situates learning in guided experience solving complex problems, such as medical diagnosis, planning instruction, or designing a playground. Developed initially for use in medical schools it has expanded to other settings such as teacher education, business, engineering, and K-12 instruction (Barrows, 2000; Hmelo-Silver, 2004; Torp & Sage, 2002).
PBL is considered a constructivist approach to instruction because in PBL, students are actively engaged in learning content, strategies, and self-directed learning skills through collaboratively solving problems, reflecting on their experiences, and engaging in self-directed inquiry. The role of the teacher is to facilitate the students' learning by providing opportunities for learners to engage in constructive processing. The students take responsibility for their own learning and for the collective progress of their collaborative group.
PRINCIPLES OF PROBLEM-BASED LEARNING
PBL was designed with five instructional goals (Barrows, 1985): to help students (1) construct flexible knowledge, (2) develop effective problem-solving skills, (3) develop self-directed learning skills, (4) become effective collaborators, and (5) become motivated to learn. Major factors in the effectiveness of PBL are having good problems that allow for extended engagement, a student-centered tutorial process, and a facilitator to help guide the learning process.
To foster learning and engagement, good PBL problems have several characteristics. They need to be complex, open-ended, and multiple solution paths; they must be realistic, connect with the learners' experiences, and allow free inquiry. Good problems require multidiscipli-nary solutions and provide feedback that allows students to evaluate the effectiveness of their knowledge, reasoning, and learning strategies. Problems should be rich enough to promote conjecture and discussion. They should motivate the students' need to learn and apply their new knowledge (Savery, 2006). As learners generate and support their ideas, they publicly express their current understanding, thus enhancing knowledge construction and preparing them for future learning.
Each problem requires a final product or performance that allows the learners to display their understanding. For example, in their 2000 study, Hmelo, Holton, and Kolodner used PBL to help middle-school students learn life science by designing artificial lungs. The students conducted experiments and used a variety of other resources to learn about breathing. Their final products were models of their designs. In teacher education, the final product might be a lesson design, whereas in medical education, it is often an explanation of underlying mechanisms that cause a patient problem.
The heart of PBL is the small group tutorial process. A PBL tutorial begins by presenting a group of students with some information about a complex problem. From the outset, students need to obtain additional problem information through engaging in inquiry. They may gather this information from problem simulations, for example from a patient record database in medical education or from a classroom video in teacher education (Derry, Hmelo-Silver, Nagarajan, Chernobilsky, & Beit-zel, 2006); they may also gather facts by doing experiments or other research. At several points, students pause to reflect on the data they have collected so far, generate questions about that data, and ideas about solutions. Students identify concepts they need to learn more about to solve the problem. After considering the problem with their current knowledge, learners divide and independently research the learning issues identified. They then Page 273 | Top of Articlecome back together to share what they learned and re-evaluate their ideas. When completing the task, they reflect on the problem to consider the lessons learned, as well as how they performed as self-directed learners and collaborative problem solvers.
As part of the tutorial process, students use whiteboards to help guide their learning and problem solving. The whiteboard is divided into four columns that help structure their activity by reminding the learners of the problem-solving process. The whiteboard serves as a focus for group discussions. The Facts column holds information that the students obtain from the problem statement and from their inquiry into the details of the problems. The Ideas column serves to keep track of their evolving hypotheses about solutions, such as difficulty breathing might be caused by asthma, a common respiratory ailment. The students place their questions for further study into the Learning Issues column. They use the Action Plan column to keep track of plans for resolving the problem or obtaining additional information. It should be noted that although this is a typical whiteboard, some schools using PBL use only the first three columns. Other schools that use PBL use KWL charts in which students indicate what they Know, what they Want to learn, and what they Learned.
The facilitator is a key factor in an effective PBL tutorial. In PBL, facilitators (also called tutors or coaches) are expert learners, able to model good learning and reasoning strategies, rather than providing content expertise. The facilitator helps move students through the various stages of PBL and monitors group dynamics, ensuring that all students are involved and encouraging them both to articulate their own thinking and to comment on one another's thinking. The facilitator plays an important role in modeling the thinking skills needed when self-assessing reasoning and understanding. It is important to note that the facilitator's moves build on students' thinking to maintain a student-centered learning process. For example, the facilitator encourages students to explain and justify their thinking as they propose solutions to problems. Facilitators guide the tutorial largely through the use of open-ended questions. Their questions help model the use of particular reasoning strategies as they encourage students to connect their inquiry to hypotheses, explain their thinking, and realize the limits of their understanding. Facilitators progressively reduce their support as students become more experienced with PBL until the facilitators' questioning role is largely adopted by the students. However, the facilitators continue to actively monitor the group, making moment-to-moment decisions about how to facilitate the PBL process using a repertoire of different strategies (Hmelo-Silver & Barrows, 2006).
RESEARCH ON PROBLEM-BASED LEARNING
Of the five goals for PBL, much of the research has focused on knowledge construction, problem-solving skills, and self-directed learning skills. There is less evidence about collaboration and motivation. The majority of the research has been conducted in the medical school context. In a 2003 analysis across many studies of PBL in medical education, Dochy and colleagues found that students in a PBL curriculum were better at applying their knowledge than students in a traditional curriculum and that there were no differences on fact-based measures. A few studies have been conducted outside the medical venue and these show some positive effects but there are too few studies to draw firm conclusions (see Hmelo-Silver, 2004 for a review).
Barrows, H. S. (1985). How to design a problem-based curriculum for the preclinical years. New York: Springer.
Barrows, H. S. (2000). Problem-based learning applied to medical education. Springfield IL: Southern Illinois University Press.
Derry, S. J., Hmelo-Silver, C. E., Nagarajan, A., Chernobilsky, E., & Beitzel, B. (2006). Cognitive transfer revisited: Can we exploit new media to solve old problems on a large scale? Journal of Educational Computing Research, 35, 145–162.
Dochy, F., Segers, M., Van den Bossche, P., & Gijbels, D. (2003). Effects of problem-based learning: A meta-analysis. Learning and Instruction, 13, 533–568.
Hmelo, C. E., Holton, D., & Kolodner, J. L. (2000). Designing to learn about complex systems. Journal of the Learning Sciences, 9, 247–298.
Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16, 235–266.
Hmelo-Silver, C. E., & Barrows, H. S. (2006). Goals and strategies of a problem-based learning facilitator. Interdisciplinary Journal of Problem-based Learning, 1, 21–39.
Savery, J. R. (2006). Overview of PBL: Definitions and distinctions. Interdisciplinary Journal of Problem-based Learning, 1, 9–20.
Torp, L., & Sage, S. (2002). Problems as possibilities: Problem-based learning for k-12 education (2nd ed.). Alexandria VA: Association for Supervision and Curriculum Development.
Cindy E. Hmelo-Silver
The use of projects in learning has a long history, dating back to the 1918 work of William Heard Kilpatrick (1871–1965). In this initial formulation, project-based learning was the idea of “whole-hearted purposeful Page 274 | Top of Articleactivity proceeding in a social environment.” Thus, many elements of project-based approaches of the twenty-first century are present in this early conception. A goal of using projects is to provide opportunities for students to become engaged in their own learning as they create meaningful artifacts. These may include reports, physical models, computer models, exhibits, Web sites and other concrete products that provide opportunities for students to demonstrate their understanding. Project-based learning (PBL) is a constructivist approach to learning because students are involved in constructing deep understanding as they engage with the ideas needed for their projects.
University of Michigan researchers Krajcik and Blumenfeld (2006) have contributed to articulating the key features of designs for PBL:
- Learners start with a driving question, such as “What's in our water?”
- They explore the driving question by engaging in inquiry. For example, they may study changes in water quality at a local stream. In this process, they learn to apply key disciplinary ideas.
- Learners work collaboratively to address the driving question.
- Learning technologies support the learners' inquiry and allow them to participate in authentic activities that might otherwise be beyond their reach.
- Learners create artifacts to address the driving question such as a computer model of a local water source.
The driving question helps learners see the relevance of what they are learning. This is important as learners are engaged in inquiry over a prolonged time period rather than the typical short-term laboratory experiences. Students need scaffolding for their inquiry, which is accomplished through teacher modeling and feedback as well as through technology-based scaffolding. A key feature of many PBL approaches is the use of technology as cognitive tools that support planning, collaboration, data collection and analysis, modeling, visualization, and information gathering. Examples of these approaches are found in the work of Linn and Slotta with the Web Integrated Science Environment (2006) and the Center for Learning Technology in Urban Schools (Krajcik & Blumenfeld, 2006). Although the research on the effectiveness of PBL overall is limited, according to Krajcik and Blumenfeld, there is growing evidence that project-based science is effective in improving student achievement and motivation.
PBL has similarities to problem-based learning and case-based learning as Savery has noted. All situate learning in real-situations that provide contexts for applying ideas (Hmelo-Silver, 2004). In case-based learning, cases are used as illustrations with a variety of different instructional strategies. There is no signature student-centered pedagogy in case-based instruction though such approaches tend to be oriented toward promoting knowledge application and critical thinking skills. There is a fine line between problem- and project-based learning. Both may involve creating artifacts, but this is not necessarily the case in problem-based learning. In problem-based learning, the problem may be more complex than in project-based learning. There are also differences in the activity structures that are used. The role of the teacher is similar in both approaches because they both build on student thinking. In both approaches, the teacher builds on student thinking, but in a project-based approach, the teacher may also provide benchmark lessons and play a larger role in setting learning goals than in problem-based learning.
Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16, 235–266.
Kilpatrick, W. H. (1918). The project method. Teachers College Record, 19, 319–33.
Krajcik, J. S., & Blumenfeld, P. C. (2006). Project-based learning. In R. K. Sawyer (Ed.), Cambridge Handbook of the Learning Sciences (pp. 317–333). New York: Cambridge University Press.
Linn, M. C., & Slotta, J. D. (2006). Enabling participants in online forums to learn from each other. In A. M. O'Donnell, C. E. Hmelo-Silver, & G. Erkens (Eds.), Collaborative learning, reasoning, and technology (pp. 61–98). Mahwah, NJ: Erlbaum.
Savery, J. R. (2006). Overview of PBL: Definitions and distinctions. Interdisciplinary Journal of Problem-based Learning, 1, 9–20.
Gale Document Number: GALE|CX3027800077