Skip to main content

The ‘Ins’ and ‘Outs’ of Learning: Internal Representations and External Visualizations

  • Chapter

Part of the book series: Models and Modeling in Science Education ((MMSE,volume 3))

Abstract

Science classrooms teach complex topics by exposing students to information through a variety of methodologies, including lectures, discussions, readings, lab experiences, and representational experiences. The goal of these activities is to help students build internal representations for course content – information stored in memory that students can retrieve to generate inferences, solve problems, and make decisions. But what are these internal representations like, and what does the nature of these representations suggest for the design of learning methodologies such as external representations? This chapter is an introduction to current and contemporary work on mental representations. In particular, we emphasize theoretical and empirical views that have focused on links between perception and action, and what those links imply for learning. In this way, basic research on the nature of memory can provide pragmatic suggestions with respect to the design, implementation, and assessment of what are commonly called ‘visualizations’ (i.e., external visual representations of processes) as tools for science learning.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Alibali, M. W. (2005). Gesture in spatial cognition: Expressing, communicating, and thinking about spatial information. Spatial Cognition and Computation, 5, 307–331.

    Article  Google Scholar 

  • Anderson, J. R., & Lebiere , C. (1998). The atomic components of thought. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Baddeley, A. D. (1986). Working memory. Oxford, UK: Clarendon Books.

    Google Scholar 

  • Baddeley, A. D. (1992). Working memory. Science, 255, 556–559.

    Article  Google Scholar 

  • Baddeley, A. D., & Hitch , G. J. (1974). Working memory. In G. H. Bower (Ed.), Recent Advances in learning and motivation (Vol. 8, pp. 47–90). New York: Academic Press.

    Google Scholar 

  • Baddeley, A. D., & Lieberman , K. (1980). Spatial working memory. In R. S. Nickerson (Ed.), Attention and performance VIII (pp. 521–539). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Baddeley, A. D., & Logic, R. H. (1999). Working memory: The multiple-component model. In A. Miyake & P. Shah (Eds.), Models of working memory (pp. 28–61). Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral & Brain Sciences, 22, 577–660.

    Article  Google Scholar 

  • Barsalou, L. W., & Hale, C. R. (1993). Components of conceptual representation: From feature lists to recursive frames. In I. Van Mechelen, J. Hampton, R. Michalski, & P. Theuns (Eds.), Categories and concepts: Theoretical views and inductive data analysis (pp. 97–144). San Diego, CA: Academic Press.

    Google Scholar 

  • Behrmann, M. (2005). The mind’s eye mapped onto the brain’s matter. In B.A. Spellman & D.T. Willingham (Eds.), Current Directions in Cognitive Science. Readings from the American Psychological Society (pp. 11–18). Upper Saddle River, NJ: Pearson Education.

    Google Scholar 

  • Brunyé, T. T., Taylor, H. A., Rapp, D. N., & Spiro, A. B. (2006). Learning procedures: The role of working memory in multimedia learning experiences. Applied Cognitive Psychology, 20, 917–940.

    Article  Google Scholar 

  • Chao, L.L., & Martin, A. (2000). Representation of manipulable man-made objects in the dorsal stream. Neuroimage, 12, 478–484.

    Article  Google Scholar 

  • Chi, M. T. H., Feltovich, P., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152.

    Google Scholar 

  • Chi, M. T. H., Glaser, R., & Farr. M. (Eds.). (1988). The nature of expertise. Hillsdale, NJ: LEA.

    Google Scholar 

  • Clark, H. H. (1996). Using language. Cambridge: Cambridge University Press.

    Google Scholar 

  • Dunn, K., & Dunn, R. (1978). Teaching students through their individual learning styles. Reston, VA: National Council of Principals.

    Google Scholar 

  • Dweck, C. (1986). Motivational processes affecting learning. American Psychologist, 41, 1040–1047.

    Article  Google Scholar 

  • Eley, M. G. (1991.) Selective encoding in the interpretation of topographic maps. Applied Cognitive Psychology, 5, 403–422.

    Article  Google Scholar 

  • Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). Psychological Review, 100, 363–406.

    Article  Google Scholar 

  • Ferretti, T. R., McRae, K., & Hatherell, A. (2001). Integrating verbs, situation Schemas, and thematic role concepts. Journal of Memory and Language, 44, 516–547.

    Article  Google Scholar 

  • Fincher-Kiefer, R. (2001). Perceptual components of situation models. Memory & Cognition, 29, 336–343.

    Google Scholar 

  • Franco, C., & Colinvaux, D. (2000). Grasping mental models. In J. K. Gilbert & C. J. Boulter (Eds.), Developing models in science education (pp. 93–118). Boston, MA: Kluwer Academic Publishers.

    Google Scholar 

  • Gerlach, C., Law, I., & Paulson, O. B. (2002). When action turns into words: Activation of motor-based knowledge during categorization of manipulable objects. Journal of Cognitive Neuroscience, 14, 1230–1239.

    Article  Google Scholar 

  • Glenberg, A. M. (1997). What memory is for. Behavioral and Brain Sciences, 20, 1–55.

    Article  Google Scholar 

  • Glenberg, A. M., Gutierrez, T., Levin, J. R., Japuntich, S., & Kaschak, M .P. (2004). Activity and imagined activity can enhance young children’s reading comprehension. Journal of Educational Psychology, 96, 424–436.

    Article  Google Scholar 

  • Glenberg, A. M., & Kaschak, M. P. (2002). Grounding language in action. Psychological Bulletin & Review, 9, 558–565.

    Google Scholar 

  • Glenberg, A. M., & Robertson, D. A. (1999). Indexical understanding of instructions. Discourse Processes, 28, 1–26.

    Article  Google Scholar 

  • Goldstone, R. L., & Sakamoto , Y. (2003). The transfer of abstract principles governing complex adaptive systems. Cognitive Psychology, 46, 414–466.

    Article  Google Scholar 

  • Graesser, A. C., & Clark, L. F. (1985). Structures and procedures of implicit knowledge. Norwood, NJ: Ablex.

    Google Scholar 

  • Grafton, S. T., Arbib, M. A., Fadiga, L., & Rizzolatti, G. (1996). Localization of grasp representations in humans by positron emission tomography – 2. Observation compared with imagination. Experimental Brain Research, 112, 103–111.

    Article  Google Scholar 

  • Harnad, S. (1990). The symbol grounding problem. Physica D, 42, 335–346.

    Google Scholar 

  • Hegarty, M. (2004). Mechanical reasoning by mental simulation. Trends in Cognitive Sciences, 8, 280–285.

    Article  Google Scholar 

  • Heiser, J., & Tversky, B. (2006). Arrows in comprehending and producing mechanical Diagrams. Cognitive Science, 30, 581–592.

    Google Scholar 

  • Hesslow, G. (2002). Conscious thought as simulation of behaviour and perception. Trends in Cognitive Sciences, 6, 242–24.

    Article  Google Scholar 

  • Horton, W. S., & Rapp, D. N. (2003). Out of sight, out of mind: Occlusion and the accessibility of information in narrative comprehension. Psychonomic Bulletin & Review, 10, 104–109.

    Google Scholar 

  • Johnson-Laird, P. N. (1980). Cognitive Science, 4, 71–115.

    Article  Google Scholar 

  • Kahneman, D., & Tversky, A. (1982). The simulation heuristic. In D. Kahneman, P. Slovic, & A. Tversky (Eds.), Judgment under uncertainty: Heuristics and biases (pp.201–208). New York: Cambridge University Press.

    Google Scholar 

  • Kaschak, M. P., Madden, C. J., Therriault, D. J., Yaxley, R. H., Aveyard, M., Blanchard, A. A., et al. (2005). Perception of motion affects language processing. Cognition, 94, B79–B89.

    Article  Google Scholar 

  • Kellenbach, M. L., Brett, M., & Patterson, K. (2001). Large, colorful, or noisy? Attribute- and modality-specific activations during retrieval of perceptual attribute knowledge. Cognitive, Affective, & Behavioral Neuroscience, 1, 207–221.

    Article  Google Scholar 

  • Kintsch, W. (1998). Comprehension: A paradigm for cognition. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Kosslyn, S. M. (1994). Image and brain: The resolution of the imagery debate. Cambridge, MA: MIT Press.

    Google Scholar 

  • Lakoff, G., & Johnson, M. (1980) Metaphors we live by. Chicago: University of Chicago Press.

    Google Scholar 

  • Levelt, W. J. M. (1989). Speaking: From intention to articulation. Cambridge, MA: MIT Press.

    Google Scholar 

  • Loftus, E. F., Miller, D. G., & Burns, H. J. (1978). Semantic integration of verbal information into a visual memory. Journal of Experimental Psychology: Human Learning and Memory, 4, 19–31.

    Article  Google Scholar 

  • Loftus, E. F., & Palmer, J. C. (1974). Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of Verbal Learning and Verbal Behavior, 13, 585–589.

    Article  Google Scholar 

  • Markman, A. B. (1999). Knowledge Representation. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Martin, A., & Chao, L. L. (2001). Semantic memory and the brain: Structure and processes. Current Opinion in Neurobiology, 11, 194–201.

    Article  Google Scholar 

  • Martin, A., Haxby, J. V., Lalonde, F. M., Wiggs, C. L., & Ungerleider, L. G. (1995) Discrete cortical regions associated with knowledge of color and knowledge of action. Science, 270, 102–105.

    Article  Google Scholar 

  • Martin, A., Wiggs, C. L., Ungerleider, L. G., & Haxby, J. V. (1996) Neural correlates of category-specific knowledge. Nature, 379, 649–652.

    Article  Google Scholar 

  • Mayer, R. E. (2001). Multimedia learning. New York: Cambridge University Press.

    Google Scholar 

  • Mayer, R. E. (2003). The promise of multimedia learning: Using the same instructional design methods across different media.Learning and Instruction, 13, 125–139.

    Article  Google Scholar 

  • Mayer, R. E., & Anderson, R. B. (1992). The instructive animation: Helping students build connections between words and pictures in multimedia learning. Journal of Educational Psychology, 84, 444–452.

    Article  Google Scholar 

  • Mayer, R. E., Heiser, J., & Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. Journal of Educational Psychology, 93, 187–198.

    Article  Google Scholar 

  • Mayer, R. E., & Moreno , R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43–52.

    Article  Google Scholar 

  • Mayer, R. E., & Sims, V. K. (1994). For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning. Journal of Educational Psychology, 86, 389–401.

    Article  Google Scholar 

  • Minsky, M. (1975). A framework for representing knowledge. In P. H. Winston (Ed.), The psychology of computer vision (pp. 211–277). New York: McGraw Hill.

    Google Scholar 

  • Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning: The role of modality and contiguity. Journal of Educational Psychology, 91, 358–368.

    Article  Google Scholar 

  • Nelson, D. L., Reed, U. S., & Walling, J. R. (1976). Picture superiority effect. Journal of Experimental Psychology: Human Learning & Memory, 2, 523–528.

    Google Scholar 

  • Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  • Norman, D. A. (1983). Some observations on mental models. In D. Gentner & A. L. Stevens (Eds.), Mental models (pp. 7–14). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Paivio, A. (1971). Imagery and verbal processes. New York: Holt, Rinehart & Winston.

    Google Scholar 

  • Paivio, A. (1983). The empirical case for dual coding. In J. C. Yulle (Ed.), Imagery, memory and cognition (pp. 307–332). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Paivio, A. (1986). Mental representations: A dual-coding approach. New York: Oxford University Press.

    Google Scholar 

  • Paivio, A. (1991). Dual coding theory: Retrospect and current status. Canadian Journal of Psychology, 45, 255–87.

    Google Scholar 

  • Paivio, A., & Csapo, K. (1973). Picture superiority effect: Imagery or dual coding? Cognitive Psychology, 5, 176–206.

    Article  Google Scholar 

  • Pecher, D., Zeelenberg, R., & Barsalou, L. W. (2003). Verifying properties from different modalities for concepts produces switching costs. Psychological Science, 14, 119–124.

    Article  Google Scholar 

  • Pick, H. L., Heinrichs, M. R., Montello, D. R., Smith, K., Sullivan, C. N., & Thompson, W. B. (1995). Topographic map reading. In P. A. Hancock, J. M., Flach, J. Caird, & K. J. Vicente (Eds.), local applications of the ecological approach to human-machine systems (pp. 255–284). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Pylyshyn, Z. W. (1981). The imagery debate: Analogue media versus tacit knowledge. Psychological Review, 88, 16–45.

    Google Scholar 

  • Pylyshyn, Z. W. (2002). Mental imagery: In search of a theory. Behavioral & Brain Sciences, 25, 157–238.

    Article  Google Scholar 

  • Rapp, D. N. (2005). Mental models: Theoretical issues for visualizations in science education. In J. K. Gilbert (Ed.), Visualization in Science Education (pp. 43–60). The Netherlands: Springer.

    Chapter  Google Scholar 

  • Rapp, D. N. (2006). The value of attention aware systems in educational settings. Computers in Human Behavior, 22, 603–614.

    Article  Google Scholar 

  • Rapp, D. N., Culpepper, S. A., Kirkby, K., & Morin, P. (in press). Fostering students’ comprehension of topographic maps. Journal of Geoscience Education.

    Google Scholar 

  • Rapp, D. N., Taylor, H. A., & Crane, G. R. (2003). The impact of digital libraries on cognitive processes: Psychological issues of hypermedia. Computers in Human Behavior, 19, 609–628.

    Article  Google Scholar 

  • Rapp, D. N., & Uttal, D. H. (2006). Understanding and enhancing visualizations: Two models of collaboration between earth science and cognitive science. In C. Manduca & D. Mogk (Eds.), Earth and mind: How geologists think and learn about the Earth (pp. 121–127). Boulder, CO: Geological Society of America Press.

    Chapter  Google Scholar 

  • Reimann, P., & Chi, M. T. H. (1989). Expertise in complex problem solving. In K. J. Gilhooly (Ed.), Human and Machine Problem Solving (pp. 161–192). New York: Plenum Press.

    Google Scholar 

  • Searle, J. R. (1980). Minds, brains, and programs. Behavioral & Brain Sciences, 3, 417–424.

    Article  Google Scholar 

  • Sloutsky, V. M., Kaminski, J. A., & Heckler, A. F. (2005). The advantage of simple symbols for learning and transfer. Psychonomic Bulletin & Review, 12, 508–513.

    Google Scholar 

  • Sperling, G. (1960). The information available in brief visual presentations. Psychological Monographs: General and Applied, 74, 1–30.

    Google Scholar 

  • Stanfield, R. A., & Zwaan, R. A. (2001). The effect of implied orientation derived from verbal context on picture recognition. Psychological Science, 12, 153–156.

    Article  Google Scholar 

  • Svensson, H., & Ziemke, T. (2004). Making sense of embodiment: Simulation theories and the sharing of neural circuitry between sensorimotor and cognitive processes. In Proceedings of the 26th annual meeting of the Cognitive Science Society.Mawhah, NJ: Erlbaum.

    Google Scholar 

  • Taylor, H. A., Renshaw, C. E., & Choi, E. J. (2004). The effect of multiple formats on understanding complex visual displays. Journal of Geoscience Education, 52, 115–121.

    Google Scholar 

  • Taylor, H. A., Renshaw, C. E., & Jensen, M. D. (1997). Effects of computer-based role-playing on decision making skills. Journal of Educational Computing Research, 17, 147–164.

    Article  Google Scholar 

  • Tversky, B. (in press). Mental models. In A. E. Kazdin (Ed.), Encyclopedia of Psychology. Washington, DC: APA Press.

    Google Scholar 

  • Tversky, B., Zacks, J. M., Lee, P. U., & Heiser, J. (2000). Lines, blobs, crosses, and arrows. In M. Anderson, P. Cheng, & V. Haarslev (Eds.), Theory and application of diagrams (pp. 221–230). Edinburgh: Springer.

    Chapter  Google Scholar 

  • Valenzeno, L., Alibali, M. W., & Klatzky, R. (2003). Teachers’ gestures facilitate students’ learning: A lesson in symmetry. Contemporary Educational Psychology, 28,187–204.

    Article  Google Scholar 

  • Van Dijk, T. A., & Kintsch, W. (1983). Strategies of discourse comprehension. New York: Academic Press.

    Google Scholar 

  • Wiemer-Hastings, K., & Xu, X. (2005). Content differences for abstract and concrete concepts. Cognitive Science, 29, 719–736.

    Google Scholar 

  • Woolfolk, A. (2004). Educational psychology (9th ed.). Boston, MA: Allyn and Bacon.

    Google Scholar 

  • Zwaan, R. A. (2004). The immersed experiencer: Toward an embodied theory of language comprehension. In B. H. Ross (Ed.), The psychology of leaning and motivation, (Vol. 4, pp. 35–62). New York: Academic Press.

    Google Scholar 

  • Zwaan, R. A., Madden, C. J., Yaxley, R. H., & Aveyard, M. E. (2004). Moving words: Dynamic mental representations in language comprehension. Cognitive Science, 28, 611–619.

    Article  Google Scholar 

  • Zwaan, R. A., Stanfield, R. A., & Yaxley, R. H. (2002). Language comprehenders routinely represent the shape of objects. Psychological Science, 13, 168–171.

    Article  Google Scholar 

  • Zwaan, R. A., & Yaxley, R. H. (2004). Spatial iconicity affects semantic-relatedness judgments. Psychonomic Bulletin & Review, 10, 954–958.

    Google Scholar 

  • Zwaan R. A., & Yaxley, R. H. (2005). Lateralization of object-shape information in semantic processing. Cognition, 94, B35–B43.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Rapp, D.N., Kurby, C.A. (2008). The ‘Ins’ and ‘Outs’ of Learning: Internal Representations and External Visualizations. In: Gilbert, J.K., Reiner, M., Nakhleh, M. (eds) Visualization: Theory and Practice in Science Education. Models and Modeling in Science Education, vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5267-5_2

Download citation

Publish with us

Policies and ethics