Advertisement

Journal of Science Education and Technology

, Volume 22, Issue 3, pp 287–299 | Cite as

Mapping Changes in Science Teachers’ Content Knowledge: Concept Maps and Authentic Professional Development

  • Barbara A. Greene
  • Ian A. Lubin
  • Janis L. Slater
  • Susan E. Walden
Article

Abstract

Two studies were conducted to examine content knowledge changes following 2 weeks of professional development that included scientific research with university scientists. Engaging teachers in scientific research is considered to be an effective way of encouraging knowledge of both inquiry pedagogy and content knowledge. We used concept maps with two cohorts of teachers to assess changes in science teacher knowledge. In study 1, 34 teachers developed pre- and post-concept maps in one of the nine different content areas. A repeated measures analysis of six quantitative scores showed statistically significant increases in knowledge representation. Quantitative and qualitative scoring methods indicate that concept maps are effective for assessing teacher knowledge gains from professional development. Study 2 replicated the results with 24 teachers and provided further information about how knowledge changes.

Keywords

Concept maps Teacher science learning Teacher professional development 

Notes

Acknowledgments

This study was a part of the Oklahoma REESE project which was made possible through the financial support of the National Science Foundation (NSF), Directorate for Education and Human Resources (EHR), Division of Research, Evaluation and Communication (REC), Grant #DRL-0634070 granted to the K20 Center for Educational Renewal (K20) at the University of Oklahoma. The K20 Center also recognizes the efforts of staff and public educators throughout the State of Oklahoma; the OU Department of Botany/Microbiology; the OU School for Civil Engineering and Environmental Science; the OU College of Education; and the OU Department of Communication, who have participated in the development of this project. Without their assistance and participation, this project would not be possible. A version of the first study summarized in this paper was presented at the Sixteenth International Conference on Learning in Barcelona. Spain (July 2009).

References

  1. Anderson JR, Pirolli PL (1984) Spread of activation. J Exp Psychol Learn Mem Cognit 10:791–798CrossRefGoogle Scholar
  2. Anderson JR, Reder LM (1979) An elaborative processing explanation of depth of processing. In: Cermak LS, Craik FIM (eds) Levels of processing in human memory. Erlbaum, Hillsdale, pp 385–403Google Scholar
  3. Armbruster B (1996) Schema theory and the design of content-area textbooks. Educ Psychol 21:253–276Google Scholar
  4. Atkinson L, Cate J, O’Hair MJ, Slater J (2009) K20 model: creating networks, professional learning communities, and communities of practice that increase science learning. In: Mundry S, Stiles K (eds) Professional learning communities for science teaching: lessons from research and practice. NSTA press, Arlington, pp 129–148Google Scholar
  5. Ausubel D (1963) The psychology of meaningful verbal learning. Grune & Stratton, New YorkGoogle Scholar
  6. Besterfield-Sacre M, Gerchak J, Lyons M, Shuman LJ, Wolfe H (2004) Scoring concept maps: an integrated rubric for assessing engineering education. J Eng Educ 93:105–115CrossRefGoogle Scholar
  7. Borko H (2004) Professional development and teacher learning: mapping the terrain. Educ Res 33(8):3–15Google Scholar
  8. Borko H, Jacobs J, Koellner K (2010) Contemporary approaches to teacher professional development. In Baker E, Peterson P, McGaw B (eds) International encyclopedia of education, 3rd edn. Elsevier Scientific Publishers, Oxford, deel 7, pp 548–555Google Scholar
  9. Bransford JD, Brown AL, Cocking RR (2000) How people learn: brain, mind, experience, and school, Expanded edn. National Academy Press, WashingtonGoogle Scholar
  10. Brumby M (1983) Concept mapping: structure or process? Res Sci Educ 13:9–17CrossRefGoogle Scholar
  11. Cohen J (1988) Statistical power analysis for the behavioral sciences, 2nd edn. Lawrence Erlbaum Associates, HillsdaleGoogle Scholar
  12. Craik FIM, Lockhart RS (1972) Levels of processing: a framework for memory research. J Verbal Learn Verbal Behav 11:671–684CrossRefGoogle Scholar
  13. Darling-Hammond L (2000) Teacher quality and student achievement: a review of state policy evidence. Educ Policy Anal Arch 8(1). http://epaa.asu.edu/epaa/v8n1
  14. Desimone LM, Porter AC, Garet M, Yoon KS, Birman B (2002) Does professional development change teachers’ instruction? Results from a three-year study. Educ Eval Policy Anal 24(2):81–112CrossRefGoogle Scholar
  15. Druva CA, Anderson RD (1983) Science teacher characteristics by teacher behavior and by student outcome: a meta-analysis of research. J Res Sci Teach 20(5):467–479CrossRefGoogle Scholar
  16. Edwards J, Fraser K (1983) Concept maps as reflectors of conceptual understanding. Res Sci Educ 13:19–26CrossRefGoogle Scholar
  17. Entwistle NJ (1998) Approaches to learning and forms of understanding. In: Dart B, Boulton-Lewis G (eds) Teaching and learning in higher education. Australian Council for Educational Research, Melbourne, pp 72–101Google Scholar
  18. Garet M, Porter A, Desimone L, Birman B, Yoon K (2001) What makes professional development effective? Results from a national sample of teachers. Am Educ Res J 38:915–945CrossRefGoogle Scholar
  19. Graff M (2005) Differences in concept mapping, hypertext architecture, and the analyst–intuition dimension of cognitive style. Educ Psychol 25:409–422CrossRefGoogle Scholar
  20. Haefner LA, Zembal-Saul C (2004) Learning by doing? Prospective elementary teachers’ developing understandings of scientific inquiry and science teaching and learning. Int J Sci Educ 26:1653–1674CrossRefGoogle Scholar
  21. Hay DB (2007) Using concept maps to measure deep, surface and non-learning outcomes. Stud High Educ 32:39–57CrossRefGoogle Scholar
  22. Hough S, O’Rode N, Terman N, Weissglass J (2007) Using concept map to assess change in teachers’ understandings of algebra: a respectful approach. J Math Teach Educ 10:23–41CrossRefGoogle Scholar
  23. Jacoby LL, Craik FIM (1979) Effects of elaboration of processing as encoding and retrieval: trace distinctiveness and recovery of initial context. In: Cermak LS, Craik RIM (eds) Levels of processing and human memory. Erlbaum, Hillsdale, pp 1–21Google Scholar
  24. Jonassen DH, Beissner K, Yacci M (1993) Structural knowledge: techniques for assessing, conveying, and acquiring structural knowledge. Lawrence Erlbaum, HillsdaleGoogle Scholar
  25. Kaya ON (2008) A student-centered approach: assessing the changes in prospective science teachers’ conceptual understanding by concept mapping in a general chemistry laboratory. Res Sci Educ 38:91–110CrossRefGoogle Scholar
  26. Kinchin IM, Hay DB, Adams A (2000) How a qualitative approach to concept map analysis can be used to aid learning by illustrating patterns of conceptual development. Educ Res 42:43–57CrossRefGoogle Scholar
  27. Lave J, Wenger E (1991) Situated learning: legitimate peripheral participation. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  28. Loucks-Horsley S, Love N, Stiles K, Mundry S, Hewson P (2003) Designing professional development for teachers of science and mathematics, 2nd edn. Corwin Press, Thousand OaksGoogle Scholar
  29. Loughran JJ, Mulhall P, Berry A (2004) In search of pedagogical content knowledge in science: developing ways of articulating and documenting professional practice. J Res Sci Teach 41(4):370–391CrossRefGoogle Scholar
  30. National Research Council (1996) The national science education standards. National Academy Press, WashingtonGoogle Scholar
  31. National Research Council (2000) Inquiry and the national science education standards. National Academy Press, WashingtonGoogle Scholar
  32. National Research Council (2005) How students learn: history, mathematics, and science in the classroom. The National Academies Press, WashingtonGoogle Scholar
  33. National Research Council (2011) A framework for K-12 science education: practices, scutting concepts, and core ideas. Committee on a Conceptual Framework for New K-12 Science Education Standards. Board on Science Education, Division of Behavioral and Social Sciences and Education. The National Academies Press, WashingtonGoogle Scholar
  34. National Science Teachers Association (2004) NSTA position statement: scientific inquiry. Retrieved 29 Mar 2011(http://www.nsta.org/pdfs/PositionStatement_ScientificInquiry.pdf)
  35. Novak JD (2005) Results and implications of a 12-year longitudinal study of science concept learning. Res Sci Educ 35:23–40CrossRefGoogle Scholar
  36. Novak JD, Cañas AJ (2008) The theory underlying concept maps and how to construct and use them. Technical Report IHMC CmapTools 2006-01 Rev 01-2008. Florida Institute for Human and Machine Cognition. Retrieved 27 May 2009. http://cmap.ihmc.us/Publications/ResearchPapers/TheoryUnderlyingConceptMapsHQ.pdf
  37. Novak JD, Gowin DB (1984) Learning how to learn. Cambridge University Press, New YorkCrossRefGoogle Scholar
  38. Putnam R, Borko H (2000) What do new views of knowledge and thinking have to say about research on teacher learning? Educ Res 21:4–15Google Scholar
  39. Ruiz-Primo MA, Shavelson RJ (1996) Problems and issues in the use of concept maps in science assessment. J Res Sci Teach 33:569–600CrossRefGoogle Scholar
  40. Russell SH, Hancock MP (2007) Evaluation of the research experiences for teachers (RET) program: 2001–2006. Final Report from SRI International. Retrieved 27 May 2009 from http://www.retnetwork.org/evaluation.php
  41. Rye JA, Rubba PA (1998) An exploration of the concept map as an interview tool to facilitate the externalization of students’ understandings about global atmospheric change. J Res Sci Teach 35:521–546CrossRefGoogle Scholar
  42. Sadler TD, Burgin S, McKinney L, Ponjuan L (2010) Learning science through research apprenticeships: a critical review of the literature. J Res Sci Teach 47(3):235–256Google Scholar
  43. Shavelson RJ, Ruiz-Primo MA, Wiley EW (2005) Windows into the mind. High Educ 49:413–430CrossRefGoogle Scholar
  44. Smith TM, Densimore LM, Zeidner TL, Dunn AC, Bhatt M, Rumyantseva NL (2007) Inquiry-oriented instruction in science: who teaches that way? Educ Eval Policy Anal 29:169–199. doi: 10.3102/0162373707306025 CrossRefGoogle Scholar
  45. Spillane JP (1999) External reform initiatives and teachers’ efforts to reconstruct their practice: the mediating role of teachers’ zones of enactment. J Curriculum Stud 31(2):143–175Google Scholar
  46. Stoddart T, Abrams R, Gasper E, Canaday D (2000) Concept maps as assessment in science inquiry learning—a report of methodology. Int J Sci Educ 22:1221–1246CrossRefGoogle Scholar
  47. Van Zele E, Lenaerts J, Wieme W (2004) Improving the usefulness of concept maps as a research tool for science education. Int J Sci Educ 26:1043–1064CrossRefGoogle Scholar
  48. Wheeler G (2007) Strategies for science education reform. Educ Leadersh 64(4):30–34Google Scholar
  49. Yin Y, Vanides J, Ruiz-Primo MA, Ayala CC, Shavelson RJ (2005) Comparison of two concept-mapping techniques: implications for scoring, interpretation, and use. J Res Sci Teach 42:166–184CrossRefGoogle Scholar
  50. Zak KM, Munson BH (2008) An exploratory study of elementary pre-service teachers’ understanding of ecology using concept maps. J Environ Educ 39:32–46CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Barbara A. Greene
    • 1
  • Ian A. Lubin
    • 1
    • 2
  • Janis L. Slater
    • 3
  • Susan E. Walden
    • 4
  1. 1.Department of Educational PsychologyUniversity of OklahomaNormanUSA
  2. 2.Georgia Southern UniversityStatesboroUSA
  3. 3.K20 CenterUniversity of OklahomaNormanUSA
  4. 4.College of EngineeringUniversity of OklahomaNormanUSA

Personalised recommendations