Cognitive research and the design of science instruction

Champagne, Audrey B.; Klopfer, Leopold E.; Gunstone, Richard

doi:10.1080/00461528209529242

Cited by 165 publications

(67 citation statements)

References 20 publications

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“…In this article, a variation on the paradigm described by Champagne et al (1982) is proposed--that is, using smallgroup discussion as the vehicle for the construction of an initial representation of the problem. Small groups of learners are given a description of a set of natural phenomena (e.g.…”

Section: Instructional Methods Aimed At Integrationmentioning

confidence: 99%

“…Subsequently, they read an expository text on the subject, attend lectures about it, or see the actual result of the experiment. Champagne, Klopfer, and Gunstone (1982), for instance, describe an approach in which students are presented with qualitative mechanics problems, such as the following: "When a gun is fired, the bullet leaves the gun with some speed. How does the bullet's speed at the muzzle of the gun compare with the gun's speed at that time?…”

Section: Instructional Methods Aimed At Integrationmentioning

confidence: 99%

See 1 more Smart Citation

Explanatory models in the processing of science text: The role of prior knowledge activation through small-group discussion.

Schmidt

Volder

Grave

et al. 1989

Journal of Educational Psychology

158

124

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Two experiments assessed effects of activation of prior knowledge through small-group discussion. Subjects were given a description of natural phenomena and were asked to elaborate on possible explanations for them. In Experiment 1, small groups of subjects were presented with a problem describing the behavior of a blood cell in pure water and in a salt solution. No additional text was studied. The experimental subjects produced more than twice as many propositions about osmosis (i.e. the biological process explaining the blood cell's behavior) as a control group produced. Experiment 2 investigated effects of problem analysis on subsequent text processing for subjects with imprecise prior knowledge (novices) and subjects with precise knowledge (experts). Recall of the text showed considerable facilitative effects of problem analysis. Results are explained in terms of faster accessibility of prior knowledge and better integration of new information into explanatory models that may exist before, or are actively constructed during, problem analysis.

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Section: Instructional Methods Aimed At Integrationmentioning

confidence: 99%

Section: Instructional Methods Aimed At Integrationmentioning

confidence: 99%

Explanatory models in the processing of science text: The role of prior knowledge activation through small-group discussion.

Schmidt

Volder

Grave

et al. 1989

Journal of Educational Psychology

158

124

View full text Add to dashboard Cite

show abstract

“…The first is that encountering contradictory information is a very common occurrence when one is learning science. Science students' preinstructional beliefs about the natural world often conflict sharply with many of the accepted scientific theories they are taught in school, and this is true across a wide variety of domains within biology, chemistry, and physics (for reviews, see Carey, 1985;Champagne, Klopfer, & Gunstone, 1982;Confrey, 1990;Driver & Easley, 1978; Driver, Guesne, & Tiberghien, 1985;Eylon & Linn, 1988;Osborne & Freyberg, 1985;Perkins & Simmons, 1988;Roth, 1990). Thus, the encounter with contradictory information is at the heart of knowledge acquisition in science.…”

Section: The Role Of Anomalous Data In Knowledge Acquisition: a Theormentioning

confidence: 99%

The Role of Anomalous Data in Knowledge Acquisition: A Theoretical Framework and Implications for Science Instruction

Chinn¹,

Brewer

1993

Review of Educational Research

993

351

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Understanding how science students respond to anomalous data is essential to understanding knowledge acquisition in science classrooms. In this report, we present a detailed analysis of the ways in which scientists and science students respond to anomalous data. We postulate that there are seven distinct forms of response to anomalous data, only one of which is to accept the data and change theories. The other six responses involve discounting the data in various ways in order to protect the preinstructional theory. We analyze the factors that influence which of these seven forms of response a scientist or student will choose, giving special attention to the factors that make theory change more likely. Finally, we discuss the implications of our framework for science instruction.Anomalous Data -2 THE ROLE OF ANOMALOUS DATA IN KNOWLEDGE ACQUISITION: A THEORETICAL FRAMEWORK AND IMPLICATIONS FOR SCIENCE INSTRUCTIONThis report addresses an issue that is crucial for understanding how people learn science and how to improve science instruction: How do students respond when they encounter scientific information that contradicts their current theories' about the physical world? In other words, how do students respond when their current beliefs about the physical world conflict with the information presented during science instruction?This issue is crucial for two reasons. The first is that encountering contradictory information is a very common occurrence when one is learning science. Science students' preinstructional beliefs about the natural world often conflict sharply with many of the accepted scientific theories they are taught in school, and this is true across a wide variety of domains within biology, chemistry, and physics (for reviews, see Carey, 1985;Champagne, Klopfer, & Gunstone, 1982;Confrey, 1990;Driver & Easley, 1978; Driver, Guesne, & Tiberghien, 1985;Eylon & Linn, 1988;Osborne & Freyberg, 1985;Perkins & Simmons, 1988;Roth, 1990). Thus, the encounter with contradictory information is at the heart of knowledge acquisition in science.The second reason why understanding how students respond to contradictory information is crucial for science education is that students typically resist giving up their preinstructional beliefs. Instead of abandoning or modifying their preinstructional beliefs in the face of new, conflicting data and ideas, students often staunchly maintain old ideas and reject or distort new ideas. For instance, some children who are told that the earth is round preserve their preinstructional belief that the earth is flat by concluding that the earth is disc shaped (Vosniadou & Brewer, 1992). Similarly, children can spend days or weeks studying photosynthesis and yet persist in their preinstructional belief that plants get their food from the soil (Anderson & Smith, 1984). And a number of researchers have found that many young adults go through high school and university physics courses without ever giving up their pre-Newtonian views of motion (e.g., Champagne, Klopfer, & Anderson...

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“…Winn promoted the use of cognitive instructional strategies, less reductionistic forms of analysis, and a more holistic approach to learner interactions as a means for achieving that view (Winn 1990). Cognitive models and processes of instructional design have emphasized mental constructs such as information processing (Champagne, Klopfer, and Gunstone 1982;Wildman and Burton 1981); schemata, knowledge structures, and other knowledge states (DiVesta and Rieber 1987); and learning strategies (Jonassen 1985). All of these models have emphasized the role of mental processing in learning.…”

mentioning

confidence: 99%

Constructivism and computer‐mediated communication in distance education

Jonassen

Davidson

Collins

et al. 1995

American Journal of Distance Education

705

357

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The fields of learning theory and instructional design are in the midst of a scientific revolution in which their objectivist philosophical foundations are being replaced by a constructivist epistemology. This article describes the assumptions of a constructivist epistemology, contrasts them with objectivist assumptions, and then describes instructional systems that can support constructive learning at a distance Limitations of Distance Learning TechnologiesIn an effort to supplement or replace live face-to-face instruction, technologicany mediated distance learning has more often than not merely replicated the ineffective methods that limit learning in face-to-face classrooms (Turoff 1995). Too often, potentially interactive technologies are used to present one-way lectures to students in remote locations. However, we believe that the most valuable activity in a classroom of any kind is the opportunity for students to work and interact together and to build and become part of a community of scholars and practitioners (Selfe and Eilola 1989;Bates 1990;Seaton 1993;Nalley 1995). A good learning experience is one in which a student can "master new knowledge and skills, criticany examine assumptions and beliefs, and engage in an invigorating, collaborative quest for wisdom and personal, holistic development" (Eastmond and Ziegahn 1995, 59). Technology used in distance education should facilitate these "good learning experiences" in an "extended classroom model" rather than broadcast teacher-centered lectures and demonstrations (Burge and Roberts 1993). A significant impediment to this goal is the fact that many teachers and instructional designers come to distance education from traditional backgrounds, bringing with them assumptions about teaching and learning that are not theory-based and do not translate well to technologicany mediated instruction (Schieman, Taere, and McLaren 1992). 7Our purpose here is to promote well-designed, mediated instruction that moves the teacher from podium to sideline, from leader to coach, from purveyor of knowledge to facilitator of personal meaning making (Romiszowski and de Haas 1989;Beaudoin 1990;Gunawardena 1992;Burge and Roberts 1993). Our belief is that technology can be used to create communities of learners and practitioners and can facilitate the interactions and activities necessary for solving real-world problems (Burge and Roberts 1993). Our focus in this paper is to show how constructivism can help us reconceptualize distance education by using the new technologies to significantly alter how we conduct distance education (Morrison and Lauzon 1992). Constructivist principles provide a set of guiding principles to help designers and teachers create learner-centered, collaborative environments that support reflective and experiential processes. Students and instructors can then build meaning, understanding, and relevant practice together and go far beyond the mere movement of information from instructors' minds to students' notebooks.

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Cognitive research and the design of science instruction

Cited by 165 publications

References 20 publications

Explanatory models in the processing of science text: The role of prior knowledge activation through small-group discussion.

Explanatory models in the processing of science text: The role of prior knowledge activation through small-group discussion.

The Role of Anomalous Data in Knowledge Acquisition: A Theoretical Framework and Implications for Science Instruction

Constructivism and computer‐mediated communication in distance education

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