Abstract
A Study with students enrolled at an urban technical college compared learning of HTML coding across three Web-based program versions. One group received examples providing factual information about the source code (Facts group). A second group was presented with a step-by-step description of the source code (Procedures group). The third group was shown a visual model, including a diagram and arrows denoting the source code and the associated outcome (Visual Model group). A comparison of coding activity revealed that the Visual Model group constructed more correct code, with fewer trials, in the same amount of time. The Visual Model group also more accurately debugged flawed code. The Procedures group coded more correctly than the Facts group but differences decreased as problem complexity increased.
Similar content being viewed by others
References
Anderson, J.R., Boyle, C.F., & Reiser, B.F. (1985). Intelligent tutoring systems.Science, 228, 456–462.
Anderson, J.R., Farrell, R., & Sauers, R. (1984). Learning to program in LISP.Cognitive Science, 8, 87–129.
Bauer, M.I., & Johnson-Laird, P.N. (1993). How diagrams can improve reasoning.Psychological Science, 4, 372–378.
Black, J.B. (1992).Types of knowledge representation (CCT Report 92–3). New York: Teachers College, Columbia University.
Chi, M.T.H., Feltovich, P.J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices.Cognitive Science, 5, 121–152.
Cohen, J. (1988).Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates, Inc.
Craik, K. (1943).The nature of explanation Cambridge: Cambridge University Press.
Gentner, D., & Stevens, A.L. (Eds.). (1983).Mental models Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
Hendrix, T.D. (1996).A framework for language independent generation of graphical representations of algorithms Doctoral dissertation. Auburn University: Auburn, Alabama.
Johnson, W.L., Soloway, E., Cutler, B., & Draper, S. (1983).Bug catalogue I., Technical Report 286, Department of Computer Science, Yale University.
Johnson-Laird, P.N. (1983).Mental models: Toward a cognitive science of language, inference, and consciousness, Boston, MA: Harvard University Press.
Jonassen, D. (2003). Using cognitive tools to represent problems.Journal of Research on Technology in Education, 35(3), 362–381.
Judd, C.M., & McClelland, G.H. (1989).Data analysis: A model-comparison approach Orlando, Florida: Harcourt Brace Jovanovich, Inc.
Kaplan, D.E. (2001).Mental model development and reasoning about a causal system in a computer-based inquiry environment Unpublished doctoral dissertation. Columbia University: New York.
Ledgard, H.F. (1975).Programming proverbs Rochell Park, NJ: Hayden.
Mayer, R.E., & Gallini, J. (1990). When is a picture worth a thousand words?Journal of Educational Psychology, 82, 715–727.
Mayer, R.E. (1993). Illustrations that instruct. In R. Glaser (Ed.),Advances in instructional psychology (Vol. 5, pp. 253–284). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
Mayer, R.E. (1997). Multimedia in learning: Are we asking the right question?Educational Psychologist, 32(1), 1–19.
Najork, M.A. (1996). Programming in three dimensions.Journal of Visual Languages and Computing, 7, 219–242.
Nielsen, M.C. (1990).The impact of informational feedback and a second attempt at practice questions on concept learning in computer-aided instruction. Doctoral dissertation, University of Texas at Austin.
Nielsen, M.C. (1990).The impact of informational feedback and a second attempt at practice questions on concept learning in computer-aided instruction. Doctoral dissertation, University of Texas at Austin.
Norman, D.A. (1983). Some observations on mental models. In D. Gentner & A.L. Stevens (Eds.),Mental models (pp. 99–129). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
Petre, M. (1995). Why looking isn’t always seeing: Readership skills and graphical programming.Communications of the ACM, 38(6), 33–44.
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.
Schwartz, D.L., & Black, J.B. (1996a). Shuttling between depictive models and abstract rules.Cognitive Science, 20, 457–497.
Schwartz, D.L., & Black, J.B. (1996b). Analog imagery in mental model reasoning: Depictive models.Cognitive Psychology, 30, 154–219.
Stokes, M.E., Davis, C.S., & Koch, G.G. (2000).Categorical data analysis using the SAS System (2nd ed.). Cary, NC: SAS Institute Inc.
Suwa, M., & Tversky, B. (1997). What do architects and students perceive in their design sketches? A protocol analysis.Design Studies, 18(4), 385–403.
Sweller, J. (1999).Instructional design in technical areas Victoria, Australia: The Australian Council for Educational Research Ltd (ACER).
Sweller, J., & Cooper, G.A. (1985). The use of worked examples as a substitute for problem solving in learning algebra.Cognition and Instruction, 2(1), 59–89.
Tung, S., & Chang, C. (2001). Visual representations for recursion.International Journal of Human-Computer Studies, 54, 285–300.
Tversky, B., Heiser, J., Lee, P., & Zacks, J. M. (2002). Diagrams to augment cognition. In W.D. Gray & CD. Shunn (Eds.),Proceedings of the 24th Annual Meeting of the Cognitive Science Society (p. 57). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Kaplan, D.E., An, H. Facts, procedures, and visual models in Novices’ learning of coding skills. J. Comput. High. Educ. 17, 43–70 (2005). https://doi.org/10.1007/BF02960226
Issue Date:
DOI: https://doi.org/10.1007/BF02960226