Skip to main content

Advertisement

SpringerLink
Log in

Effects of conceptual, procedural, and declarative reflection on students’ structural knowledge in physics

  • Research Article
  • Published:
Educational Technology Research and Development Aims and scope Submit manuscript

Abstract

Reflection has recently been emphasized as a constructive pedagogical activity. However, little attention has been given to the quality of reflections that students write. In this study, we explored the reflections that students make about their knowledge organization as part of a formative learning activity. More specifically, we assessed the knowledge structures of Grade 11 physics students and their instructors using pathfinder networks (PFnets). Each student’s knowledge structure was compared with the instructors’ averaged knowledge structure in order to identify student misconceptions. As an intervention, students were asked to write reflections on the discrepancies between their knowledge structure and their instructors’ averaged knowledge structure. The students’ reflections were divided into the following three categories depending on the type of knowledge constructed in those reflections: (1) conceptual, (2) procedural, or (3) declarative. Evidence was provided by the study that reflection was an effective means of improving students’ knowledge structure. However, conceptual reflections were the most effective, followed by procedural and declarative reflection. Implications for formative classroom assessment are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Akerson, V. L., Flick, L. B., & Lederman, N. G. (2000). The influence of primary children’s ideas in science on teaching practice. Journal of Research in Science Education, 37, 363–385.

    Google Scholar 

  • Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An integrated theory of the mind. Psychological Review, 111(4), 1036–1060.

    Article  Google Scholar 

  • Apt, K. R., Blair, H. A., & Walker, A. (1988). Towards a theory of declarative knowledge. In R. Hull & M. Yoshikawa, Declarative Creation and Manipulation of Object Identifiers . Proceeding: VLDB ‘90 Proceedings of the 16th International Conference on Very Large Data Bases (pp. 89–148)

  • Azzarello, J. (2007). Use of the pathfinder scaling algorithm to measure students’ structural knowledge of community health nursing. Journal of Nursing Education, 46(7), 313–318.

    Google Scholar 

  • Baird, J. R. (1986). Improving learning through enhanced metacognition: A classroom study. European Journal of Science Education, 8(3), 263–282.

    Article  Google Scholar 

  • Baird, J. R., Fensham, P. J., Gunstone, R. F., & White, R. T. (1991). The importance of reflection in improving science teaching and learning. Journal of Research in Science Teaching, 28(2), 163–182.

    Article  Google Scholar 

  • Baxter, G. P., Elder, A. D., & Glaser, R. (1996). Knowledge-based cognition and performance assessment in the science classroom. Educational Psychologist, 31, 133–140.

    Article  Google Scholar 

  • Biglan, A. (1973). The characteristics of subject matter in different academic areas. Journal of Applied Psychology, 57, 204–213.

    Article  Google Scholar 

  • Black, P., & McCormick, R. (2010). Reflections and new directions. Assessment & Evaluation in Higher Education, 35(5), 493–499.

    Article  Google Scholar 

  • Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21(1), 5–31.

    Article  Google Scholar 

  • Bleakley, A. (2000). Writing with invisible ink: Narrative, confessionalism and reflective practice. Reflective Practice, 1(1), 11–24.

    Article  Google Scholar 

  • Boud, D., Keogh, R., & Walker, D. (1985). Promoting reflection in learning: A model. In D. Boud, R. Keogh, & D. Walker (Eds.), Reflection: Turning experience into learning (pp. 18–40). London: Kogan Page.

    Google Scholar 

  • Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13, 145–182.

    Article  Google Scholar 

  • Clariana, R. B., Wallace, P. E., & Godshalk, V. M. (2009). Deriving and measuring group knowledge structure from essays: The effects of anaphoric reference. Educational Technology Research and Development, 57, 725–737.

    Article  Google Scholar 

  • d’Appolonia, S. T., Charles, E. S., & Boyd, G. M. (2004). Acquisition of complex systemic thinking: Mental models of evolution. Educational Research and Evaluation, 10, 499–521.

    Article  Google Scholar 

  • Day, E. A., Arthur, W., & Gettman, D. (2001). Knowledge structures and the acquisition of a complex skill. Journal of Applied Psychology, 86(5), 1022–1033.

    Article  Google Scholar 

  • Dewey, J. (1933). How We Think. Boston: D. C. Heath.

    Google Scholar 

  • Diekhoff, G. M. (1983). Testing through relationship judgments. Journal of Educational Psychology, 75(2), 227–233.

    Article  Google Scholar 

  • Engelbrecht, J., Harding, A., & Potgieter, M. (2005). Undergraduate students’ performance and confidence in procedural and conceptual mathematics. International Journal of Mathematical Education in Science and Technology, 36(7), 701–712.

    Article  Google Scholar 

  • Ertmer, P. A., & Newby, T. J. (1996). The expert learner: Strategic, self-regulated, and reflective. Instructional Science, 24(1), 1–24.

    Article  Google Scholar 

  • Frese, M., & Zapf, D. (1994). Action as the core of work psychology: A German approach. In H. C. Triandis, M. D. Dunnette, & L. M. Hough (Eds.), Handbook of industrial and organizational psychology (2nd ed., Vol. 4, pp. 271–340). Palo Alto: Consulting Psychologists Press.

    Google Scholar 

  • Goldman, S., & Hasselbring, T. (1997). Achieving meaningful mathematics literacy for students with learning disabilities. Journal of Learning Disabilities, 30(2), 198–208.

    Article  Google Scholar 

  • Goldsmith, T. E., Johnson, P. J., & Acton, W. H. (1991). Assessing structural knowledge. Journal of Educational Psychology, 83(1), 88–96.

    Article  Google Scholar 

  • Good, R. (2011). Formative use of assessment information: It’s a process, so let’s say what we mean. Practical Assessment, Research & Evaluation, 16(3). http://pareonline.net/getvn.asp?v=16&n=3. Accessed 25 March 2013.

  • Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112.

    Article  Google Scholar 

  • Hay, D. B., Tan, P. L., & Whaites, E. (2010). Non-traditional learners in higher education: Comparison of a traditional MCQ examination with concept mapping to assess learning in a dental radiological science course. Assessment & Evaluation in Higher Education, 35(5), 577–595.

    Article  Google Scholar 

  • Holly, C. D., & Dansereau, D. F. (Eds.). (1984). Spatial learning strategies: Techniques, applications, and related issues. Orlando: Academic Press.

    Google Scholar 

  • Jonassen, D. H., & Wang, S. (1993). Acquiring structural knowledge from semantically structured hypertext. Journal of Computer-Based Instruction, 20(1), 19–28.

    Google Scholar 

  • Kadijevich, Dj, & Haapasalo, L. (2001). Linking procedural and conceptual mathematical knowledge through CAL. Journal of Computer Assisted learning, 17(2), 156–165.

    Article  Google Scholar 

  • Keppens, J., & Hay, D. (2008). Concept map assessment for teaching computer programming. Computer Science Education, 18(1), 31–42.

    Article  Google Scholar 

  • Krause, U. M., & Stark, R. (2010). Reflection in example- and problem-based learning: effects of reflection prompts, feedback and cooperative learning. Evaluation & Research in Education, 23(4), 255–272.

    Article  Google Scholar 

  • Kudikyala, U. K. (2004). Reducing misunderstanding of software requirements by conceptualization of mental models using pathfinder networks. Dissertation Abstract International, 65(07), 3542A. (UMI No. AAT 3141998). Dissertations and Theses database. Accessed 20 August 2009.

  • Kuiper, R., & Pesut, D. (2004). Promoting cognitive and metacognitive reflective reasoning skills in nursing practice: Self-regulated learning theory. Journal of Advanced Nursing, 45(4), 381–391.

    Article  Google Scholar 

  • Mathieu, J. E., Heffner, T. S., Goodwin, G. F., Cannon-Bowers, J. A., & Salas, E. (2005). Scaling the quality of teammates’ mental models: Equifinality and normative comparisons. Journal of Organizational Behavior, 26, 37–56.

    Article  Google Scholar 

  • Mayer, R. E. (2001). Cognitive, metacognitive, and motivational aspects of problem solving. In H. J. Hartman (Ed.), Metacognition in learning and instruction (pp. 87–101). Norwell: Kluwer Academic.

    Chapter  Google Scholar 

  • McGaghie, W. C., McCrimmon, D. R., Mitchell, G., Thompson, J. A., & Ravitch, M. M. (2000). Quantitative concept mapping in pulmonary physiology: comparison of student and faculty knowledge structures. Advances in Physiology Education, 23(1), 72–81.

    Google Scholar 

  • Meyer, D. E., & Schvaneveldt, R. W. (1976). Meaning, memory structure, and mental processes. Science, 192(4234), 27–33.

    Article  Google Scholar 

  • Moore, A. (2004). The good teacher: Dominant discourses in teaching and teacher education. London: Routledge.

    Book  Google Scholar 

  • Morris, S. B., & DeShon, R. P. (2002). Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs. Psychological Methods, 7(1), 105–125.

    Article  Google Scholar 

  • Morton, R. F., Hebel, J. R., & McCarter, R. J. (1996). A study guide to epidemiology and biostatistics. Gaithersburg: Aspen Publishers.

    Google Scholar 

  • Nagy, P. (1984). Cognitive structure and the spatial metaphor. In P. Nagy (Ed.), The Representation of Cognitive Structure (pp. 1–11). Toronto: Ontario Institute for Studies in Education.

    Google Scholar 

  • National Research Council. (2001). Knowing what students know: The science and design of educational assessment. Washington: National Academy Press.

    Google Scholar 

  • Novak, J. D. (1990a). Concept maps and vee diagrams: Two metacognitive tools to facilitate meaningful learning. Instructional Science, 19(1), 29–52.

    Article  Google Scholar 

  • Novak, J. D. (1990b). Concept mapping: A useful tool for science education. Journal of Research in Science Teaching, 27(10), 937–950.

    Article  Google Scholar 

  • Novak, J. D., & Cañas, A. J. (2008). The theory underlying concept maps and how to construct them. Institute for Human and Machine Cognition. http://cmap.ihmc.us/docs/theory-of-concept-maps. Accessed 17 August 2014.

  • O’Reilly, T., Symons, S., & MacLatchy-Gaudet, H. (1998). A comparison of self-explanation and elaborative interrogation. Contemporary Educational Psychology, 23(4), 434–445.

    Article  Google Scholar 

  • Ramsey, C. (2005). Narrative from learning in reflection to learning in performance. Management Learning, 36(2), 219–235.

    Article  Google Scholar 

  • Roy, M., & Chi, M. T. H. (2005). The self-explanation principle in multi-media learning. In R. E. Mayer (Ed.), Cambridge handbook of multimedia learning (pp. 271–287). Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Sadler, D. R. (2010). Beyond feedback: developing student capability in complex appraisal. Assessment & Evaluation in Higher Education, 35(5), 535–550.

    Article  Google Scholar 

  • Sarwar, G. S. (2011). Structural assessment of knowledge for misconceptions: Effectiveness of structural feedback provided by pathfinder networks in the domain of physics. Kolln, Germany: LAP Lambert Academic Publishing.

    Google Scholar 

  • Schau, C., Mattern, N.,Weber, R. W., Minnick, K., & Witt, C. (1997, April). Use of fill-in concept maps to assess middle school students’ connected understanding of science. Paper presented at the annual meeting of the American Educational Research Association, Chicago.

  • Schön, D. A. (1983). The Reflective Practitioner. London: Temple Smith.

    Google Scholar 

  • Schvaneveldt, R. W. (Ed.). (1990). Pathfinder associative networks: Studies in knowledge organization. Norwood: Ablex Publishing Corp.

    Google Scholar 

  • Siegler, R. S. (2002). Microgenetic studies of self-explanation. In N. Granott & J. Parziale (Eds.), Microdevelopment: Transition processes in development and learning (pp. 31–58). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • Soloman, J. (1987). New thoughts on teacher education. Oxford Review of Education, 13(3), 267–274.

    Article  Google Scholar 

  • Trochim, W. M. (1989a). An introduction to concept mapping for planning and evaluation. Evaluation and Program Planning, 12(1), 1–16.

    Article  Google Scholar 

  • Trochim, W. M. (1989b). Concept mapping: Soft science or hard art? http://www.socialresearchmethods.net/research/epp2/epp2.htm. Accessed 20 January 2014.

  • Trumpower, D. L., & Goldsmith, T. E. (2004). Structural enhancement of learning. Contemporary Educational Psychology, 29(4), 426–446.

    Article  Google Scholar 

  • Trumpower, D. L., & Sarwar, G. S. (2010a). Effectiveness of structural feedback provided by Pathfinder networks. Journal of Educational Computing Research, 43(1), 7–24.

    Article  Google Scholar 

  • Trumpower, D. L., & Sarwar, G. S. (2010b). Formative structural assessment: Using concept maps as assessment for learning. Paper presented at the Fourth International Conference on Concept Mapping, Vina del Mar, Chile. Retrieved January 22, 2013, from http://cmc.ihmc.us/cmc2010papers/cmc2010-214.pdf.

  • Trumpower, D. L., Sharara, H., & Goldsmith, T. E. (2010). Specificity of structural assessment of knowledge. Journal of Teaching, Learning, and Assessment, 8(5), 1–32.

    Google Scholar 

  • Williams, M. (2004). Concept mapping: A strategy for assessment. Nursing Standard, 19(9), 33–38.

    Article  Google Scholar 

  • Wittgenstein, L. (1953). Philosophical Investigations. Oxford: Basil Blackwell.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Education, University of Ottawa, 145 Jean-Jacques-Lussier Street, Ottawa, ON, K1N 6N5, Canada

    Gul Shahzad Sarwar

  2. Faculty of Education, University of Ottawa, Lamoureux Hall Room 430, 145 Jean-Jacques-Lussier Street, Ottawa, ON, K1N 6N5, Canada

    David L. Trumpower

Authors
  1. Gul Shahzad Sarwar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David L. Trumpower
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gul Shahzad Sarwar.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sarwar, G.S., Trumpower, D.L. Effects of conceptual, procedural, and declarative reflection on students’ structural knowledge in physics. Education Tech Research Dev 63, 185–201 (2015). https://doi.org/10.1007/s11423-015-9368-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11423-015-9368-7

Keywords

Search

Navigation