Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-10T10:16:39.123Z Has data issue: false hasContentIssue false

15 - The Knowledge Integration Perspective on Learning and Instruction

Published online by Cambridge University Press:  05 June 2012

Marcia C. Linn
Affiliation:
University of California
R. Keith Sawyer
Affiliation:
Washington University, St Louis
Get access

Summary

The knowledge integration perspective emerged from studies of the conceptions of scientific phenomena that students bring to science class, from design studies refining science instruction, and from longitudinal studies of students' learning over weeks, months, and years. These studies stress that learners grapple with multiple, conflicting, and often confusing, ideas about scientific phenomena. They characterize learners as developing a repertoire of ideas, adding new ideas from instruction, experience, or social interactions, sorting out these ideas in varied contexts, making connections among ideas at multiple levels of analysis, developing more and more nuanced criteria for evaluating ideas, and formulating an increasingly linked set of views about any phenomenon.

The knowledge integration perspective capitalizes on the varied ideas held by students both individually and collectively to stimulate science learning. The knowledge integration perspective synthesizes recent investigations of science learning and instruction, culminating in a set of design patterns that promote coherent and cohesive understanding, and design principles that guide customization of patterns. This chapter describes the process of knowledge integration and how knowledge integration resonates with current research programs. It offers guidance to researchers and curriculum designers wishing to promote lifelong science learning.

Learning and Knowledge Integration

My colleagues and I conducted over forty case studies of middle school students who were studying thermodynamics (Clark & Linn, 2003; Linn & Hsi, 2000). These studies illustrate the typical process of knowledge integration. We found that students generate a repertoire of ideas about each concept they are learning and about the links between concepts.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

AAUW. (2000). Tech-savvy: Educating girls in the new computer age. Washington, DC: AAUW.
Aleven, V. A., & Koedinger, K. R. (2002). An effective metacognitive strategy: Learning by doing and explaining with a computer-based cognitive tutor. Cognitive Science, 26, 147–179.CrossRefGoogle Scholar
Bell, P., & Linn, M. C. (2002). Beliefs about science: How does science instruction contribute? In Hofer, B. K. & Pintrich, P. R. (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 321–346). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Bjork, R. A. (1999). Assessing our own competence: Heuristics and illusions. In Gopher, D. & Koriat, A. (Eds.), Attention and performance XVII. Cognitive regulation of performance: Interaction of theory and application (pp. 435–459). Cambridge, MA: MIT Press.Google Scholar
Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (2000). How people learn: Brain, mind, experience, and school. Washington, DC: National Research Council.Google Scholar
Brown, A. L., & Campione, J. C. (1994). Guided discovery in a community of learners. In McGilly, K. (Ed.), Classroom lessons: Integrating cognitive theory and classroom practice (pp. 229–270). Cambridge, MA: MIT Press/Bradford Books.Google Scholar
Carey, S. (1992). The origin and evolution of everyday concepts. In Giere, R. N. (Ed.), Cognitive models of science (Vol. XV, pp. 89–128). Minneapolis: University of Minnesota Press.Google Scholar
Case, R. (1985). Intellectual development: Birth to adulthood. Orlando, FL: Academic Press.Google Scholar
Chi, M. T. H. (1996). Constructing self-explanations and scaffolded explanations in tutoring. Applied Cognitive Psychology, 10, S33–S49.3.0.CO;2-E>CrossRefGoogle Scholar
Clancy, M., Titterton, N., Ryan, C., Slotta, J., & Linn, M. C. (2003). New roles for students, instructors, and computers in a lab-based introductory programming course. ACM SIGCSE Bulletin, 35(1), 132–136.CrossRefGoogle Scholar
Clark, D. B., & Linn, M. C. (2003). Scaffolding knowledge integration through curricular depth. Journal of Learning Sciences, 12(4), 451–494.CrossRefGoogle Scholar
Clement, J. (1993). Using bridging analogies and anchoring intuitions to deal with students' preconceptions in physics. Journal of Research in Science Teaching, 30(10), 1241–1257.CrossRefGoogle Scholar
Cohen, E. G. (1994). Restructuring the classroom: Conditions for productive small groups. Review of Educational Research, 64(1), 1–35.CrossRefGoogle Scholar
Collins, A., Brown, J. S., & Holum, A. (1988). The computer as a tool for learning through reflection. In Mandl, H. & Lesgold, A. M. (Eds.), Learning issues for intelligent tutoring systems (pp. 1–18). Chicago: Springer-Verlag.CrossRefGoogle Scholar
Crouch, C. H., & Mazur, E. (2001). Peer instruction: Ten years of experience and results. American Journal of Physics, 69, 970–977.CrossRefGoogle Scholar
Davis, E. (2003). Knowledge integration in science teaching: Analysing teachers' knowledge development. Research in Science Education, 34(1), 21–53.CrossRefGoogle Scholar
Davis, E. A., & Linn, M. C. (2000). Scaffolding students' knowledge integration: Prompts for reflection in KIE. International Journal of Science Education, 22(8), 819–837.CrossRefGoogle Scholar
Design-Based Research Collective. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5–8.CrossRef
diSessa, A. (1988). Knowledge in pieces. In Forman, G. & Pufall, P. (Eds.), Constructivism in the computer age (pp. 49–70). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
diSessa, A. A. (2000). Changing minds: Computers, learning and literacy. Cambridge, MA: MIT Press.Google Scholar
diSessa, A., Elby, A., & Hammer, D. (2002). J's epistemological stance and strategies. In Sinatra, G. M. & Pintrich, P. R. (Eds.), Intentional Conceptual Change (pp. 237–290). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
diSessa, A. A., Gillespie, N. M., & Esterly, J. B. (2004). Coherence versus fragmentation in the development of the concept of force. Cognitive Science, 28, 843–900.CrossRefGoogle Scholar
diSessa, A. A., & Minstrell, J. (1998). Cultivating conceptual change with benchmark lessons. In Greeno, J. G. & Goldman, S. (Eds.), Thinking practices (pp. 155–187). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Eylon, B. S., & Linn, M. C. (1988). Learning and instruction: An examination of four research perspectives in science education. Review of Educational Research, 58(3), 251–301.CrossRefGoogle Scholar
Gopnik, A., & Wellman, H. M. (1994). The theory theory. In Hirschfeld, L. A. & Gelman, S. A. (Eds.), Mapping the mind: Domain specificity in cognition and culture (pp. 257–293). New York: Cambridge University Press.CrossRefGoogle Scholar
Greeno, J., Collins, A, and Resnick, L. (1996). Cognition and learning. In Calfee, D. B. a. R. (Ed.), Handbook of educational psychology (pp. 15–46). New York: Macmillan.Google Scholar
Howe, C., Tolmie, A., Duchak-Tanner, V., & Rattray, C. (2000). Hypothesis testing in science: Group consensus and the acquisition of conceptual and procedural knowledge. Learning and Instruction, 10, 361–391.CrossRefGoogle Scholar
Inhelder, B., & Piaget, J. (1958/1972). The growth of logical thinking from childhood to adolescence; An essay on the construction of formal operational structures. New York: Basic Books.Google Scholar
Kali, Y., Bos, N., Linn, M. C., Underwood, J., & Hewitt, J. (2002). Design principles for educational software. In Stahl, G. (Ed.), Computer support for collaborative learning: Foundations for a CSCL community (Proceedings of CSCL 2002) (pp. 679–680). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Kali, Y., Orion, N., & Eylon, B. (2003). The effect of knowledge integration activities on students' perception of the earth's crust as a cyclic system. Journal of Research in Science Teaching, 40(6), 415–442.CrossRefGoogle Scholar
Kintsch, W. (1998). Comprehension: a paradigm for cognition. Cambridge, MA: MIT Press.Google Scholar
Krajcik, J. S., Blumenfeld, P. C., Marx, R. W., & Soloway, E. (1999). Instructional, curricular, and technological supports for inquiry in science classrooms. In Minstrell, J. & Zee, E. V. (Eds.), Inquiry into inquiry: Science learning and teaching. (pp. 283–315). Washington, DC: AAAS Press.Google Scholar
Lagemann, E. C. (2000). An elusive science: The troubling history of education research. Chicago: University of Chicago Press.Google Scholar
Lewis, E. L., & Linn, M. C. (1994). Heat energy and temperature concepts of adolescents, adults, and experts: Implications for curricular improvements. Journal of Research in Science Teaching, 31(6), 657–677.CrossRefGoogle Scholar
Linn, M. C. (1970). Effects of a training procedure on matrix performance and on transfer tasks. Unpublished doctoral dissertation, Stanford University, Stanford, CA.Google Scholar
Linn, M. C. (1995). Designing computer learning environments for engineering and computer science: The Scaffolded Knowledge Integration framework. Journal of Science Education and Technology, 4(2), 103–126.CrossRefGoogle Scholar
Linn, M. C. (2005). WISE design for lifelong learning-pivotal cases. In Gärdenfors, P. & Johannsson, P. (Eds.), Cognition, education and communication technology (pp. 223–256). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Linn, M. C., & Clancy, M. J. (1992). The case for case studies of programming problems. Communications of the ACM, 35(3), 121–132.CrossRefGoogle Scholar
Linn, M. C., Clark, D., & Slotta, J. D. (2003). WISE design for knowledge integration. Science Education, 87, 517–538.CrossRefGoogle Scholar
Linn, M. C., Clement, C., & Pulos, S. (1983). Is it formal if it's not physics? Journal of Research in Science Teaching, 20(8), 755–770.CrossRefGoogle Scholar
Linn, M. C., Davis, E. A., & Bell, P. (Eds.). (2004). Internet environments for science education. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Linn, M. C., & Eylon, B.-S. (in press). Science education: Integrating views of learning and instruction. In Alexander, P. A. & Winne, P. H. (Eds.), Handbook of educational psychology (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Linn, M. C., & Hsi, S. (2000). Computers, teachers, peers: Science learning partners. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Linn, M. C., & Slotta, J. D. (2006). Enabling participants in on-line forums to learn from each other. In Donnell, A. M. O', Hmelo-Silver,, C. E. & Erkens, G. (Eds.), Collaborative learning, reasoning, and technology. Mahwah, New Jersey: Lawrence Erlbaum Associates.Google Scholar
Linn, M. C., Songer, N. B., & Eylon, B. S. (1996). Shifts and convergences in science learning and instruction. In Calfee, R. & Berliner, D. (Eds.), Handbook of educational psychology (pp. 438–490). Riverside, NJ: Macmillan.Google Scholar
Masnick, A. M., & Klahr, D. (2003). Error matters: An initial exploration of elementary school children's understanding of experimental error. Journal of Cognition and Development, 4, 67–98.CrossRefGoogle Scholar
Metz, K. (2000). Young children's inquiry in biology. Building the knowledge bases to empower independent inquiry. In Minstrell, J. & Zee, E. (Eds.), Inquiring into inquiry learning and teaching in science (pp. 3–13). Washington, DC: American Association for the Advancement of Science.Google Scholar
Millar, R., & Driver, R. (1987). Beyond processes. Studies in Science Education, 14(9), 33–62.CrossRefGoogle Scholar
Osborne, J. F., & Young, A. R. (1998). The biological effects of ultra-violet radiation: A model for contemporary science education. Journal of Biological Education, 33(1), 10–15.CrossRefGoogle Scholar
Palinscar, A. S., Magnusson, S., & Cutter, J. (2001). Making science accessible to all: Results of a design experiment in inclusive classrooms. Learning Disability Quarterly, 24, 15–32.Google Scholar
Pallant, A., & Tinker, R. (2004). Reasoning with atomic-scale molecular dynamic models. Journal of Science Education and Technology, 13(1), 51–66.CrossRefGoogle Scholar
Pedone, R., Hummel, J. E., & Holyoak, K. J. (2001). The use of diagrams in analogical problem solving. Memory and Cognition, 29, 214–221.CrossRefGoogle ScholarPubMed
Pfundt, H., & Duit, R. (1991). Students' alternative frameworks (3rd ed.). Federal Republic of Germany: Institute for Science Education at the University of Kiel/Institut für die Pädagogik der Naturwissenschaften.
Piaget, J. (1970). Structuralism. New York: Basic Books.Google Scholar
Polman, J. L. (2000). Designing project-based science: Connecting learners through guided inquiry. New York: Teachers College Press.Google Scholar
Redish, E. F. (2003). Teaching physics with the physics suite. New York: John Wiley and Sons, Inc.Google Scholar
Resnick, M. (1994). Turtles, termites, and traffic jams: Explorations in massively parallel microworlds. Cambridge, MA: MIT Press.Google Scholar
Richland, L. E., Bjork, R. A., Finley, J. R., & Linn, M. C. (2005). Linking cognitive science to education: Generation and interleaving effects. In Bara, B. G., Barsalou, L. & Bucciarelli, M. (Eds.), Proceedings of the twenty-seventh annual conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Scardamalia, M., & Bereiter, C. (1991). Higher levels of agency for children in knowledge-building: A challenge for the design of new knowledge media. Journal of the Learning Sciences, 1, 37–68.CrossRefGoogle Scholar
Schofield, J. W. (1995). Computers and classroom culture. New York: Cambridge University Press.CrossRefGoogle Scholar
Shonkoff, J. P., & Phillips, D. A. (Eds.). (2000). From neurons to neighborhoods: The science of early childhood development. Washington, DC: National Academy Press.Google Scholar
Siegler, R. S. (1996). Emerging minds: The process of change in children's thinking. New York: Oxford University Press.Google Scholar
Sisk-Hilton, S. (2002). We'll take the parts that make sense: The evolution of an inquiry-oriented professional development model. In Bell, P., Stevens, R. & Satwicz, T. (Eds.), Keeping learning complex: Proceedings of the fifth international conference of the learning sciences (ICLS). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Sokoloff, D. R., & Thornton, R. K. (2004). Interactive lecture demonstrations in introductory physics. New York: John Wiley and Sons.Google Scholar
Songer, N. (1996). Exploring learning opportunities in coordinated network-enhanced classrooms – A case of kids as global scientists. Journal of the Learning Sciences, 5(4), 297–327.CrossRefGoogle Scholar
Songer, N. B., & Linn, M. C. (1992). How do students' views of science influence knowledge integration? In Pearsall, M. K. (Ed.), Scope, sequence and coordination of secondary school science, Volume I: Relevant research (pp. 197–219). Washington, DC: The National Science Teachers Association.Google Scholar
Steele, C. M. (1999). Thin ice: “Stereotype threat” and black college students. Atlantic Monthly, 44–54.Google Scholar
Strike, K. A., & Posner, G. J. (1985). A conceptual change view of learning and understanding. In West, L. H. & Pines, A. L. (Eds.), Cognitive structure and conceptual change (pp. 211–231). Orlando, FL: Academic Press.Google Scholar
Thompson, P. W. (2002). Didactic objects and didactic models in radical constructivism. In Gravemeijer, K., Lehrer, R., Oers, B. v. & Verschaffel, L. (Eds.), Symbolizing and modeling in mathematics education (pp. 191–212). Dordrecht, The Netherlands: Kluwer.CrossRefGoogle Scholar
Vosniadou, S., Ioannides, C., Dimitrakopoulou, A., & Papademetriou, E. (2001). Designing learning environments to promote conceptual change in science. Learning and Instruction, 11(4–5), 381–419.CrossRefGoogle Scholar
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.Google Scholar
White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition and Instruction, 16(1), 3–118.CrossRefGoogle Scholar
White, R., & Gunstone, R. (1992). Probing understanding. New York: Falmer Press.Google Scholar
Williams, M., Linn, M., Ammon, P., & Gearhart, M. (2004). Learning to teach inquiry science in a technology-based environment: A case study. Journal of Science Education and Technology, 13(2), 189–206.CrossRefGoogle Scholar
Zimmerman, T. (2005). Promoting knowledge integration of scientific principles and environmental stewardship: Assessing an issue-based approach to teaching evolution and marine conservation. Unpublished Doctoral Dissertation, University of California, Berkeley.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×