Educational Psychology Review

, Volume 27, Issue 3, pp 483–504 | Cite as

The Power of Examples: Illustrative Examples Enhance Conceptual Learning of Declarative Concepts

  • Katherine A. RawsonEmail author
  • Ruthann C. Thomas
  • Larry L. Jacoby


Declarative concepts (i.e., key terms with short definitions of the abstract concepts denoted by those terms) are a common kind of information that students are expected to learn in many domains. A common pedagogical approach for supporting learning of declarative concepts involves presenting students with concrete examples that illustrate how the abstract concepts can be instantiated in real-world situations. However, minimal prior research has examined whether illustrative examples actually enhance declarative concept learning, and the available outcomes provide weak evidence at best. In the three experiments reported here, students studied definitions of declarative concepts followed either by illustrative examples of those concepts or by additional study of the definitions. On a subsequent classification test in which learners were presented with examples and were asked to identify which concept the example illustrated, performance was greater for students who had studied illustrative examples during learning than for students who only studied definitions (ds from 0.74 to 1.67). However, the effects of illustrative examples on declarative concept learning depended in part on the conditions under which those examples were presented. Although performance was similar when examples were presented after versus before concept definitions (Experiments 1a–1b), classification accuracy depended on the extent to which examples of different concepts were interleaved and whether definitions were presented along with the examples (Experiment 2).


Declarative concepts Examples Concept learning Classification 



The research reported here was supported by a James S. McDonnell Foundation 21st Century Science Initiative in Bridging Brain, Mind and Behavior Collaborative Award.


  1. Allen, S. W., & Brooks, L. R. (1991). Specializing the operation of an explicit rule. Journal of Experimental Psychology: General, 120, 3–19.CrossRefGoogle Scholar
  2. Brooks, L. R., Norman, G. R., & Allen, S. W. (1991). Role of specific similarity in a medical diagnosis task. Journal of Experimental Psychology: General, 120, 278–287.CrossRefGoogle Scholar
  3. Carmines, E. G., & Zeller, R. A. (1979). Reliability and validity assessment. Thousand Oaks: Sage.CrossRefGoogle Scholar
  4. Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132, 354–380.CrossRefGoogle Scholar
  5. Cortina, J. M., & Nouri, H. (2000). Effect size for ANOVA designs. Thousand Oaks: Sage.Google Scholar
  6. DeCaro, M. S., & Rittle-Johnson, B. (2012). Exploring mathematics problems prepares children to learn from instruction. Journal of Experimental Child Psychology, 113, 552–568.CrossRefGoogle Scholar
  7. Di Vesta, F. J., & Peverly, S. T. (1984). The effects of encoding variability, processing activity, and rule-examples sequence on the transfer of conceptual rules. Journal of Educational Psychology, 76, 108–119.CrossRefGoogle Scholar
  8. Dunlosky, J., & Metcalfe, J. (2009). Metacognition. Beverly Hills: Sage.Google Scholar
  9. Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 4–58.CrossRefGoogle Scholar
  10. Griffin, M. M. (1993). Do student-generated rational sets of examples facilitate concept acquisition? Journal of Experimental Education, 61, 104–115.CrossRefGoogle Scholar
  11. Hambrick, D. Z. (2003). Why are some people more knowledgeable than others? A longitudinal study of knowledge acquisition. Memory & Cognition, 31, 902–917.CrossRefGoogle Scholar
  12. Hambrick, D. Z., Meinz, E. J., Pink, J. E., Pettibone, J. C., & Oswald, F. L. (2010). Learning outside the laboratory: Ability and non-ability influences on acquiring political knowledge. Learning and Individual Differences, 20, 40–45.CrossRefGoogle Scholar
  13. Hamilton, R. (1990). The effect of elaboration on the acquisition of conceptual problem-solving skills from prose. Journal of Experimental Education, 58, 5–17.CrossRefGoogle Scholar
  14. Hestenes, D., Wells, M., & Swackhamer, G. (1992). Force concept inventory. The Physics Teacher, 30, 141–158.CrossRefGoogle Scholar
  15. Jacoby, L. L., Wahlheim, C. N., & Coane, J. H. (2010). Test-enhanced learning of natural concepts: Effects on recognition memory, classification, and metacognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36, 1441–1451.Google Scholar
  16. Judd, C. M., & McClelland, G. H. (1989). Data analysis: A model comparison approach. New York: Harcourt Brace Jovanovich.Google Scholar
  17. Kalyuga, S., Rikers, R., & Paas, F. (2012). Educational implications of expertise reversal effects in learning and performance of complex cognitive and sensorimotor skills. Educational Psychology Review, 24, 313–337.CrossRefGoogle Scholar
  18. Kaminski, J. A., Sloutsky, V. M., & Heckler, A. F. (2013). The cost of concreteness: The effect of nonessential information on analogical transfer. Journal of Experimental Psychology: Applied, 19, 14–29.Google Scholar
  19. Karpicke, J. D., & Blunt, J. R. (2011). Retrieval practice produces more learning than elaborative studying with concept mapping. Science, 331, 772–775.CrossRefGoogle Scholar
  20. Kintsch, W. (1998). Comprehension: A paradigm for cognition. Cambridge: Cambridge University Press.Google Scholar
  21. Klausmeier, H. J., & Feldman, K. V. (1975). Effects of a definition and a varying number of examples and nonexamples on concept attainment. Journal of Educational Psychology, 67, 174–178.CrossRefGoogle Scholar
  22. Libarkin, J. (2008). Concept inventories in higher education science. National Research Council, Promising Practices in Undergraduate STEM Education Workshop 2.Google Scholar
  23. Medin, D. L., & Schaffer, M. M. (1978). Context theory of classification learning. Psychological Review, 85, 207–238. 31 pgs.CrossRefGoogle Scholar
  24. Morris, C. D., Bransford, J. D., & Franks, J. J. (1977). Levels of processing versus transfer appropriate processing. Journal of Verbal Learning and Verbal Behavior, 16, 519–533.CrossRefGoogle Scholar
  25. Murphy, G. (2004). The big book of concepts. Cambridge: MIT Press.Google Scholar
  26. Myers, D. G. (2010). Psychology: Ninth Edition. New York: Worth Publishers.Google Scholar
  27. Needham, D. R., & Begg, I. M. (1991). Problem-oriented training promotes spontaneous analogical transfer: Memory-oriented training promotes memory for training. Memory & Cognition, 19, 543–557.Google Scholar
  28. Nosofsky, R. M. (1999). Examplar-based accounts of relations between classification, recognition, and typicality. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, 700–708.Google Scholar
  29. Paas, F. G. W. C., & Van Merriënboer, J. J. G. (1994). Variability of worked examples and transfer of geometrical problem-solving skills: A cognitive-load approach. Journal of Educational Psychology, 86, 122–133. Google Scholar
  30. Pashler, H., & Harris, C. R. (2012). Is the replicability crisis overblown? Three arguments examined. Perspectives on Psychological Science, 7, 531–536.CrossRefGoogle Scholar
  31. Peterson, D. J., & Mulligan, N. W. (2013). The negative testing effect and multifactor account. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 1287–1293.Google Scholar
  32. Rawson, K. A., & Dunlosky, J. (2012). When is practice testing most effective for improving the durability and efficiency of student learning? Educational Psychology Review, 24, 419–435.CrossRefGoogle Scholar
  33. Reder, L. M., & Anderson, J. R. (1982). Effects of spacing and embellishment on memory for the main points of a text. Memory & Cognition, 10, 97–102.CrossRefGoogle Scholar
  34. Reed, S. K., & Bolstad, C. A. (1991). Use of examples and procedures in problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17, 753–766.Google Scholar
  35. Rittle-Johnson, B., & Star, J. R. (2011). The power of comparison in learning and instruction: Learning outcomes supported by different types of comparisons. In J. P. Mestre & B. H. Ross (Eds.), Psychology of learning and motivation: Cognition in education (Vol. 55, pp. 199–222). San Diego: Elsevier.Google Scholar
  36. Roediger, H. L., Weldon, M. S., & Challis, B. H. (1989). Explaining dissociations between implicit and explicit measures of retention: A processing account. In H. L. Roediger III & F. I. M. Craik (Eds.), Varieties of memory and consciousness: Essays in honour of Endel Tulving (pp. 3–41). Hillsdale: Erlbaum.Google Scholar
  37. Rohrer, D. (2012). Interleaving helps students distinguish among similar concepts. Educational Psychology Review, 24, 355–367.CrossRefGoogle Scholar
  38. Rosch, E., & Mervis, C. B. (1975). Family resemblances: Studies in the internal structure of categories. Cognitive Psychology, 7, 573–605.CrossRefGoogle Scholar
  39. Schacter, D. L., Gilbert, D. T. & Wegner, D. M. (2009). Psychology. New York: Worth Publishers.Google Scholar
  40. Schwartz, D. L., Chase, C. C., Oppezzo, M. A., & Chin, D. B. (2011). Practicing versus inventing with contrasting cases: The effects of telling first on learning and transfer. Journal of Educational Psychology, 103, 759–775.CrossRefGoogle Scholar
  41. Spilich, G. J., Vesonder, G. T., Chiesi, H. L., & Voss, J. F. (1979). Text processing of domain-related information for individuals with high and low domain knowledge. Journal of Verbal Learning and Verbal Behavior, 18, 565–583.CrossRefGoogle Scholar
  42. Taylor, K., & Rohrer, D. (2010). The effects of interleaved practice. Applied Cognitive Psychology, 24, 837–848.CrossRefGoogle Scholar
  43. van den Broek, P. (2010). Using texts in science education: Cognitive processes and knowledge representation. Science, 328, 453–456.CrossRefGoogle Scholar
  44. Zachary, R. (1986). Shipley Institute of living scale revised manual. Los Angeles: Western Psychological Services.Google Scholar
  45. Zimbardo, P. G., Johnson, R. L. & McCann, V. (2012). Psychology: Core Concepts (Seventh Edition). Upper Saddle River, NJ: Pearson.Google Scholar
  46. Zwaan, R. A., & Radvansky, G. A. (1998). Situation models in language comprehension and memory. Psychological Bulletin, 123, 162–185.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Katherine A. Rawson
    • 1
    Email author
  • Ruthann C. Thomas
    • 2
  • Larry L. Jacoby
    • 3
  1. 1.Department of PsychologyKent State UniversityKentUSA
  2. 2.Hendrix CollegeConwayUSA
  3. 3.Washington University in St. LouisSaint LouisUSA

Personalised recommendations