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Concept Mapping as a Window into Student Understanding

Concept Mapping as a Window into Student Understanding. William Cliff Department of Biology Niagara University. Biology Scholars Program SoTL Institute July, 2010. Types of Conceptual Learning. Meaningful Learning

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Concept Mapping as a Window into Student Understanding

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  1. Concept Mapping as a Window into Student Understanding William Cliff Department of Biology Niagara University Biology Scholars Program SoTL Institute July, 2010

  2. Types of Conceptual Learning • Meaningful Learning • New concepts are linked to existing knowledge in a highly integrated framework of ideas • Rote Learning • New concepts are minimally linked to existing knowledge and are stored in an arbitrary, verbatim and nonsubstantive fashion From: Mintzes J. Concept Mapping in College Science. Mintzes J and Leonard W, eds. Handbook of College Science Teaching. NSTA Press, 2006.

  3. What is a Concept Map? • A 2D node-link-node diagram that depicts the most important concepts and propositions in a knowledge domain • A network of propositions where related concepts are interlinked by labeled lines

  4. Concept Map of Concept Mapping Modified from: Novak JD & Canas AJ (2006) http//cmap.ihmc.us/Publications/Research Papers/TheoryUnderlyingConceptMaps.pdf

  5. Concept Maps as Measuring Tools • Task • Student Response Format • Scoring System

  6. Mapping Tasks • Fill-in skeleton map • Fill-in nodes (concepts) • Fill-in links (verbs) • Selected or free response • Self generated • Concepts provided • De novo

  7. Example of Mapping TaskFill-in Nodes What are the cardiovascular factors that determine mean arterial pressure (MAP)? MAP

  8. Example of Mapping TaskFill-in Links

  9. Self Generated Mapping Exercise

  10. Self Generated Map

  11. How can Concept Maps be Evaluated or Scored? • Holistically or qualitatively • Quantitatively by scoring rubrics • Structural Complexity • Content Validity • Comparison with expert maps

  12. Scoring Concept Maps

  13. Structural Scoring Method First level of Hierarchy Second level of Hierarchy Propositions score 1 x 8 = 8 Hierarchies score 5 x 2 = 10 Cross-links score 10 x 1 = 10 Examples score 1 x 2 = 2 Total = 30 McClure, JR et al. J. Res. Sci. Teach. 36:475, 1999

  14. Concept Map of Concept Mapping Modified from: Novak JD & Canas AJ (2006) http//cmap.ihmc.us/Publications/Research Papers/TheoryUnderlyingConceptMaps.pdf

  15. Structural Scoring Rubric Propositions score 1 Hierarchies score 5 Cross-links score 10 Examples score 1 McClure, JR et al. J. Res. Sci. Teach. 36:475, 1999

  16. Concept Map of Concept Mapping Propositions score 1 x 14 = 14 Hierarchies score 5 x 3 = 15 Cross-links score 10 x 3 = 30 Examples score 1 x 2 = 2 Total = 61 1st Level 2nd Level 2nd Level Crosslink 3rd Level 3rd Level 3rd Level Crosslink Example Example Crosslink Modified from: Novak JD & Canas AJ (2006) http//cmap.ihmc.us/Publications/Research Papers/TheoryUnderlyingConceptMaps.pdf

  17. Relational Scoring Method West, DC et al. Med. Educ. 36:820, 2002

  18. Valid relation score 1 x 0 = 0 Correct relation score 2 x 1 = 2 Peripheral relation score 1 x 2 = 2 Core relation score 23 x 3 = 69 Total = 74 90% Total relation score 27 x 3 = 81

  19. Assessment Exercise

  20. Example of Expert Map from Silverthorn D. Human Physiology. An Integrated Approach. 2007

  21. Expert Criterion Map

  22. Student Maps

  23. Causal Links between Cardiovascular Parameters on Student Concept Maps. N= 71 maps Cliff, W. Using concept mapping to assess understanding of cardiovascular physiology. FASEB J. 18:300.6, 2004.

  24. Summary and Conclusions

  25. Advantages of Concept Mappingfor Assessing Student Learning • Makes visible the complex structure of student’s declarative knowledge • Uncovers student misunderstandings • Reveals student conceptual change

  26. Recommendations Student Training Task Selection Scoring Analysis

  27. Further Resources • M. Zeilik. Concept Mapping. [online] www.wcer.wisc.edu/archive/cl1/flag/cat/catframe • J. Mintzes and W. Leonard, eds.Handbook of College Science Teaching. NSTA Press, 2006. • M. Ruiz-Primo and R. Shavelson. Problems and Issues in the Use of Concept Maps in Science Assessment. J. Res. Sci. Teaching. 33:569-600, 1996. • J. Nesbit and O. Adesope. Learning with Concept and Knowledge Maps: A Meta-Analysis. Rev. Edu. Res. 76:413-448, 2006.

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