Skip to main content
Log in

On the Role of Concepts in Learning and Instructional Design

  • Published:
Educational Technology Research and Development Aims and scope Submit manuscript

Abstract

The field of instructional design has traditionally treated concepts as discrete learning outcomes. Theoretically, learning concepts requires correctly isolating and applying attributes of specific objects into their correct categories. Similarity views of concept learning are unable to account for all of the rules governing concept formation, patterns of concepts, and concepts-in-use. Probabilistic-prototype and exemplar views have accommodated some of the inherent fuzziness of concepts. Concepts can only be fully understood as processes of conceptual change, the reorganization of conceptual frameworks. Although very little research has focused on assessing conceptual change, the theories of conceptual change recommend assessing patterns of concepts and concepts-in-use. Descriptions of pertinent assessment methods are presented.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Anderson, R. C. & Pichert, J. W. (1978). Recall of previously unrecallable information following a shift in perspective. Journal of Verbal Learning and Verbal Behaviour, 17, 1–12

    Article  Google Scholar 

  • Besterfield-Sacre, M., Gerchak, J., Lyons, M. R., Shuman, L. J., & Wolfe, H. (2004). Scoring concept maps: An integrated rubric for assessing engineering education. Journal of Engineering Education, 93(2), 105–115.

    Google Scholar 

  • Canelos, J, Taylor, W., & Altschuld, J. (1982). Networking vs. rote learning strategies in concept acquisition. Educational Communication and Technology—A Journal of Theory, Research, and Development, 30(3), 141–149.

  • Carey, S. (1985). Conceptual change in childhood. Cambridge, MA: MIT Press.

    Google Scholar 

  • Carrier, C., Davidson, G., & Williams, M. (1985). The selection of instructional options in a computer-based coordinate concept lesson. Educational Communication and TechnologyA Journal of Theory, Research, and Development, 33 (3), 199–212.

    Google Scholar 

  • Chan, C., Burtis, J, & Bereiter, C. (1997). Knowledge building as a mediator of conceptual change. Cognition & Instruction, 15(1), 1–40.

    Article  Google Scholar 

  • Chinn, C. A., & Brewer, W. F. (1993)). The role of anomalous data in knowledge acquisition: A theoretical framework and implications for science education. Review of Educational Research, 63, 1–49.

    Article  Google Scholar 

  • Cooke, N. M., & Schvaneveldt, R. W. (1988). Effects of computer programming experience on network representations of abstract programming concepts. International Journal of Man-Machine Studies, 29, 407–427.

    Google Scholar 

  • Edmundson, K. M. (2000). Assessing science understanding through concept maps. In J. J. Mintzes, J. H. Wandersee, J. D. Novak (Eds.), Assessing science understanding: A human constructivist view (pp. 19–40). San Diego: Academic Press.

    Google Scholar 

  • Evans, A. W., Hitt, J. M., & Jentsch, F. (2001, March). Mental model reliability. Paper presented at the APA Division 21 and 19 Mid-year Meeting, Crystal City, VA.

  • Gagné, R. M. (1966). The conditions of learning. New York: Holt, Rinehart, & Winston.

    Google Scholar 

  • Gagné, R. M. (1968). Learning hierarchies. Educational Psychologist 6, 1–9.

    Article  Google Scholar 

  • Gagné, R. M. (1973) Learning and instructional sequence. In F. N. Kerlinger (Ed.) Review of Research in Education. Itasca, IL: Peacock.

    Google Scholar 

  • Gagné, R. M., & Briggs, L. J., (1979). Principles of instructional design (2nd. ed.). Fort Worth, TX: Harcourt Brace Jovanovich.

    Google Scholar 

  • Gärdenfors, P. 2000. Conceptual spaces: the geometry of thought. Cambridge, MA: MIT Press.

    Google Scholar 

  • Gilbert, J., & Watts, D. M. (1983). Concepts, misconceptions and alternative conceptions: Changing perspectives in science education. Studies in Science Education, 10, 61–98.

    Google Scholar 

  • Haller, H. (2004). Toolvergleich Retrieved June 5, 2004 from the University of T_bingen, Instit_t fur Wissenmedien website: http://heikohaller.de/toolvergleich/.

  • Harper, M. E., Jentsch, F. G., Berry, D. Lau, H. C., Bowers, C., Salas, E. (2003). TPL-KATS-card sort: A tool for assessing structural knowledge. Behavior Research Methods, Instruments, & Computers. 35(4), 577–584.

    Google Scholar 

  • Hicken, S., Sullivan, H., & Klein, J. (1992). Learner control modes and incentive variations in computer-delivered instruction. Educational Technology: Research and Development, 40(4), 15–26.

    Article  Google Scholar 

  • Hogan, K., & Fisherkeller, J. (2000). Dialogue as data: Assessing students' scientific reasoning with interactive protocols. In J. J. Mintzes, J. H. Wandersee, J. D. Novak (Eds.), Assessing science understanding: A human constructivist view (pp. 96–129). San Diego: Academic Press.

    Google Scholar 

  • Jonassen, D. H. (1978). Implications of multi-image for concept acquisition. Educational Communication and Technology—A Journal of Theory, Research, and Development, 27(4), 291–302.

    Google Scholar 

  • Jonassen, D. H. (1986, November). Attribute identification versus example comparison strategies in an interactive videodisc concept lesson. Association for the Development of Com-puter-based Instructional Systems, Washington, DC.

  • Jonassen, D. H. (1987). Verifying a method for assessing cognitive structure using pattern notes. Journal of Research and Development in Education, 20(3), 1–14.

    Google Scholar 

  • Jonassen, D. H. (2000). Computers as Mindtools for Schools: Engaging Critical Thinking. Columbus, OH: Prentice-Hall.

    Google Scholar 

  • Jonassen, D. H. (2004). Learning to solve problems: An instructional design guide. San Francisco, CA: Pfeiffer/Jossey-Bass.

    Google Scholar 

  • Jonassen, D. H., Beissner, K., & Yacci, M. (1993). Structural knowledge: Techniques for assessing, conveying, and acquiring structural knowledge. Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Jonassen, D. H., Reeves, T. C., Hong, N., Dyer, D., & Peters, K. M. (1997). Concept mapping as cognitive learning and assessment tools. Journal of Interactive Learning Research., 8(3/4), 289–308.

    Google Scholar 

  • Jonassen, D. H., Strobel, J., & Gottdenker, J. (2005). Model building for conceptual change. Interactive Learning Environments.

  • Kelly, G. A. (1963). A theory of personality: The psychology of personal constructs. New york: W. W. Norton.

    Google Scholar 

  • Limon, M., & Mason, L. (2002). Reconsidering conceptual change: Issues in theory and practice. Amsterdam: Kluwer.

    Google Scholar 

  • Liu, X. (in press). Using concept mapping for assessing and promoting relational conceptual change in science. Science Education.

  • Mazur, J. M. (2004). Conversation analysis for educational technologists: theoretical and methodological issues for researching the structures, processes and meaning of online talk. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Medin, D. L. (1989). Concepts and conceptual structure. American Psychologist, 44(12), 1469–1481.

    Article  Google Scholar 

  • Merrill, M. D. (1983). Component display theory. In C. M. Reigeluth (Ed.), lnstructional design theories and models: An overview of their current status. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Merrill, M. D. (1987). The new component design theory: Instructional design for courseware authoring. Instructional Science, 16, 19–34.

    Article  Google Scholar 

  • Merrill, M. D., Reigeluth, C. M., & Faust, G. W. (1979). The instructional quality profile: Curriculum evaluation and design. In H. F. O'Neal (Ed.), Procedures for instructional systems development. New York: Academic Press.

    Google Scholar 

  • Merrill, M. D., Richards, R. E., Schmidt, R. & Wood, N. D. (1977). The instructional strategy diagnostic profile training manual. Provo, UT: Brigham Young University, David O. McKay Institute.

    Google Scholar 

  • Merrill, M. D., Tennyson, R. D., & Posey, L. O. (1992). Teaching concepts: An instructional design guide, 2nd Ed. Englewood Cliffs, NJ: Educational Technology Publications.

    Google Scholar 

  • Montague, W. E. (1983). Instructional quality inventory. Performance and Instruction, 22(5), 11–14.

    Google Scholar 

  • Murphy, G. L., & Medin, D. L. 1985. The role of theories in conceptual coherence. Psychological Review, 92, 289–316.

    Article  Google Scholar 

  • Newby, T. J., Ertmer, P. A., & Stepich, D. A. (1995). Instructional analogies and the learning of concepts. Educational Technology Research and Development, 43(1), 5–18.

    Article  Google Scholar 

  • Norman, D. A., Gentner, S. & Stevens, A. L. (1976). Comments on learning schemata and memory representation. In D.Klahr (Ed.), Cognition and instruction. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Quillian, M. R. (1968). Semantic memory. In M. Minsky (Ed.), Semantic information processing. Cambridge, MA: MIT Press

  • Rosch, E. (1978). Principles of categorization. In E. Rosch & B. B. Lloyd (Eds.), Cognition and categorization. Hillsdale, NJ: Lawrence Erlbaum Associates.

  • Ross, B. H., & Spalding, T. L. (1994). Concepts and categories. In R. J. Sternberg (Ed.), Thinking and problem solving (pp. 119–148). New York: Academic Press.

    Google Scholar 

  • Ruiz-Primo, M. A., Shavelson, R. J. (1996). Comparison of the reliability and validity of scores from two concept-mapping techniques. Journal of Research in Science Teaching, 38 (2), 260–278.

    Article  Google Scholar 

  • Schnotz, W., Vosniadou, S. & Carreter (1999). New perspectives in conceptual change. Amsterdam: Pergamon.

    Google Scholar 

  • Schvaneveldt, R. W., Dearholt, D. W., & Durso, F. T.(1988). Graph theoretic foundations of Pathfinder networks. Computers and Mathematics with Applications, 15, 337–345.

    Article  Google Scholar 

  • Schvaneveldt, R. W., Durso, F. T., Goldsmith, T. E., Breen, T. J., Cooke, N. M., Tucker, R. G., & DeMaio, J. C. (1985). Measuring the structure of expertise. International Journal of Man-Machine Studies, 23, 699–728.

    Article  Google Scholar 

  • Shavelson, R. J. (1972). Some aspects of the correspondence between content structure and cognitive structure in physics instruction. Journal of Educational Psychology, 63, 225–234.

    Google Scholar 

  • Siegler, R. S. (1996). Emerging minds: The process of change in children's thinking. New York: Oxford University Press.

    Google Scholar 

  • Sinatra, G. M., & Pintrich, P. R. (2003). The role of intentions in conceptual change learning. In G. M. Sinatra, & P. R. Pintrich (Eds.), Intentional conceptual change. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Smith, J. P., di Sessa, A. A., Roschelle, J. (193). Misconceptions reconceived: A constructivist analysis of knowledge in transition. Journal of Learning Sciences, 3, 115–163.

    Google Scholar 

  • Southerland, S. A., Smith, M. U., & Cummins, C. L. (2000). “What do you mean by that?”: Using structured interviews to assess science understanding. In J. J. Mintzes, J. H. Wandersee, J. D. Novak (Eds.), Assessing science understanding: A human constructivist view (pp. 72–95). San Diego: Academic Press.

    Google Scholar 

  • Strike, KA, & Posner, GJ (1985). A conceptual change view of learning and understanding. In LHT West & AL Pines (Eds.), Cognitive structure and conceptual change. (pp. 211–231). New York: Academic.

    Google Scholar 

  • Tennyson, R. D. (1978). Pictorial support and specific instructions as design variables for children's concept and rule learning. Educational Communication and TechnologyA Journal of Theory, Research, and Development, 26 (4), 291–299.

    Google Scholar 

  • Tennyson, R. D., & Buttrey, T (1980). Advisement and management strategies as design variables in computer-assisted instruction. Educational Communication and TechnologyA Journal of Theory, Research, and Development, 28 (3), 169–176.

    Google Scholar 

  • Tennyson, R. D., & Cocchiarella, M. J. (1986). An empirically based instructional design theory for teaching concepts. Review of Educational Research, 56(1), 40–71.

    Article  Google Scholar 

  • Tennyson, R. D., Youngers, J., & Suebsonthi, P. (1983). Acquisition of mathematical concepts by children using prototype and skill development presentation forms. Journal of Educational Psychology, 75, 280–291.

    Article  Google Scholar 

  • Tessmer, M., & Driscoll, M. P. (1986). Effects of diagrammatic display of coordinate concept definitions on concept classification performance. Educational Communication and Technology—A Journal of Theory, Research, and Development, 24(4), 195–205.

    Google Scholar 

  • Tessmer, M., Wilson, B., & Driscoll, M. (1990). A new model of concept learning and teaching. Educational Technology Research and Development, 38(1), 45–53.

    Article  Google Scholar 

  • Thagard, P. (1992). Conceptual revolutions. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Thro, M. P. (1978). Individual differences among college students in cognitive structure and physics performance. Paper presented at the annual meeting of the American Educational Research Association, Toronto, Canada.

  • Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction, 4(1), 45–70.

    Article  Google Scholar 

  • Vosniadou, S. (1999). Conceptual change research: The state of the art and future directions In W. Schnotz, S. Vosniadou, & M. Carretero (Eds.), New perspectives on conceptual change (pp. 1–13). Amsterdam: Pergamon.

    Google Scholar 

  • Vosniadou, S., & Brewer, W. F. (1992). Mental models of the earth: A study of conceptual change in childhood. Cognitive Psychology, 24, 535–585.

    Article  Google Scholar 

  • Whimby, A., & Lockhead, J. (1999). Problem solving and comprehension, 6th Ed. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Wittgenstein, L. (1953). Philosophical investigations, 2nd Ed (Translated by G. E. M. Anscombe). London: Blackwell Publishers.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to David H. Jonassen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jonassen, D.H. On the Role of Concepts in Learning and Instructional Design. EDUCATION TECH RESEARCH DEV 54, 177–196 (2006). https://doi.org/10.1007/s11423-006-8253-9

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11423-006-8253-9

Keywords

Navigation