Abstract
Concept map analysis usually focuses only on the final product. This case study used a talk aloud protocol to study the concept map construction processes of novices and experts. Three biology experts and three novices (9th/10th grade high school students) constructed a concept map from a given list of concepts. Findings suggest that final concept maps of high performing students cannot be distinguished from expert-generated maps. However, analysis of oral elaborations during the construction process revealed that experts often used the same link labels as novices but associated more complex knowledge with the label. Some final propositions would be considered incorrect without an oral explanation. Findings suggest extending concept map evaluation by complementing the final product with an analysis of intermediate stages and accompanying elaborations. Additionally, this study highlights that each expert created a different map and that there is no single best expert map.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Shavelson, R.J., Ruiz-Primo, M.A., Wiley, E.W.: Windows into the mind. High. Educ. 49(4), 413–430 (2005)
Bransford, J., Brown, A.L., Crocking, R.R.: How People Learn: Brain, Mind, Experience, and School, Expanded edn. National Academy Press, Washington, D.C. (2000)
Novak, J.D., Gowin, D.B.: Learning How to Learn. Cambridge University Press, Cambridge (1984)
Halford, G.S.: Children’s Understanding: The Development of Mental Models. Lawrence Erlbaum Associates, Australia Hillsdale (1993)
Chi, M.T.H., Feltovich, P., Glaser, R.: Categorization and representation of physics problems by experts and novices. Cogn. Sci. 5, 121–151 (1981)
Mintzes, J.J., Wandersee, J.H., Novak, J.D.: Meaningful learning in science: the human constructivist perspective. In: Handbook of Academic Learning: Construction of Knowledge. The Educational Psychology Series, pp. 405–447. Department of Biological Science, U North Carolina, Wilmington. Academic Press, US San Diego (1977)
Leinhardt, G., Zaslavsky, O., Stein, M.K.: Functions, graphs, and graphing: tasks, learning, and teaching. Rev. Educ. Res. 60(1), 1–63 (1990). Special Issue: Toward a Unified Approach to Learning as a Multisource Phenomenon
Parnafes, O., diSessa, A.A.: Relations between types of reasoning and computational representations. Int. J. Comput. Math. Learn. 9(3), 251–280 (2004)
Ericsson, K.A., Simon, H.A.: Protocol Analysis: Verbal Reports as Data. MIT Press, Cambridge (1985)
Ruiz-Primo, M.A., Schultz, S.E., Li, M., Shavelson, R.J.: Comparison of the reliability and validity of scores from two concept-mapping techniques. J. Res. Sci. Teach. 38(2), 260–278 (2001)
Levine, R.: Cognitive Lab Report (Report Prepared for the National Assessment Governing Board). American Institutes for Research, Palo Alto (1998)
Ayala, C.C., Yin, Y., Shavelson, R.J., Vanides, J.: Investigating the cognitive validity of science performance assessment with think alouds: technical aspects. In: American Educational Researcher Association, New Orleans, LA (2002)
Baxter, G.P., Glaser, R.: Investigating the cognitive complexity of science assessments. Educ. Measur.: Issues Pract. 17(3), 37–45 (1998)
Schwendimann, B.A., Linn, M.C.: Comparing two forms of concept map critique activities to facilitate knowledge integration processes in evolution education. J. Res. Sci. Teach. 53, 70–94 (2015)
Royer, R., Royer, J.: Comparing hand drawn and computer generated concept mapping. J. Comput. Math. Sci. Teach. 23(1), 67–81 (2004)
Inspiration (2016)
Wisdom Soft: AutoScreenRecorder 2.0. [Computer Software] (2016)
Maton, K., Doran, Y.J.: Semantic Density: A Translation Device for Revealing Complexity of Knowledge Practices in Discourse, Part 1 - Wording, Onomázein, August 2016 (in press)
Ariew, A.: Ernst Mayr’s ‘Ultimate/Proximate’ distinction reconsidered and reconstructed. Biol. Philos. 18(4), 553–565 (2003)
Ruiz-Primo, M.A., Iverson, H., Yin, Y.: Towards the use of concept maps in large-scale assessments: exploring the efficiency of two scoring methods. In: NARST Conference (2009)
Cañas, A.J., Novak, J.D., Reiska, P.: Freedom vs. restriction of content and structure during concept mapping–possibilities and limitations for construction and assessment. In: Proceedings of 5th International Conference on Concept Mapping, pp. 247–257 (2012)
Yin, Y., Vanides, J., Ruiz-Primo, M.A., Ayala, C.C., Shavelson, R.J.: Comparison of two concept-mapping techniques: implications for scoring, interpretation, and use. J. Res. Sci. Teach. 42(2), 166–184 (2005)
Kinchin, I.M.: Concept mapping in biology. J. Biol. Educ. 34(2), 61–68 (2000)
Acton, W.H., Johnson, P.J., Goldsmith, T.E.: Structural knowledge assessment - comparison of referent structures. J. Educ. Psychol. 86(2), 303–311 (1994)
Hmelo-Silver, C.E., Marathe, S., Liu, L.: Fish swim, rocks sit, and lungs breathe: expert–novice understanding of complex systems. J. Learn. Sci. 16(3), 307–331 (2007)
Schwendimann, B.A.: Making sense of knowledge integration maps. In: Ifenthaler, D., Hanewald, R. (eds.) Digital Knowledge Maps in Education: Technology Enhanced Support for Teachers and Learners. Springer, New York (2014)
Acknowledgements
The research for this paper was supported by the National Science Foundation grant DRL-0334199 (“The Educational Accelerator: Technology Enhanced Learning in Science”). I thank my advisor Prof. Marcia C. Linn for her mentorship during the research for this paper and Prof. Pierre Dillenbourg for his support leading to the publication of this paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Schwendimann, B.A. (2016). Comparing Expert and Novice Concept Map Construction Through a Talk-Aloud Protocol. In: Cañas, A., Reiska, P., Novak, J. (eds) Innovating with Concept Mapping. CMC 2016. Communications in Computer and Information Science, vol 635. Springer, Cham. https://doi.org/10.1007/978-3-319-45501-3_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-45501-3_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-45500-6
Online ISBN: 978-3-319-45501-3
eBook Packages: Computer ScienceComputer Science (R0)