Research and practice models in education
Research and practice (R<-->P) models in education refer to frameworks and practice that articulate the relationship between theory and practice.
2 The Burkhardt and Schoenfeld typology and model
This section summarizes some thoughts and findings from Burkhardt and Schoenfeld(2003)
2.1 Typology of research and practice in education
Model 1: Teachers read research and implement it in their classrooms.
- Doesn't work since teachers do not have time to read much research, make sense of it, and then use it productively in a classroom. (Magidson, 2002).
Model 2: Summary guides
- These guides are often produced by either professional organization or support centres. Not very explicit and not enough to be useful.
Model 3: General professional development
- Long-term professional development for teachers can be effective if text materials provided are consistent. (Briars, 2001; Briars & Resnick, 2000).
Model 4: The policy route.
- Doesn't work well, since accelerated diagnosis of causes is inevitably speculative, time scales are not effective, policy can outrun the research base, etc. (Dillon, 2003).
Model 5: The long route
- There can be a productive dialectic between educational research and practice. (E.g. Gardner, 1985; Senk & Thompson, 2002).)
- Time scale for substantial R<-->P impact in this case was 25 years, and that evidence on the real impact of such curricula is just beginning to accumulate.
Model 6: Design experiments.
- “Design experiments represent a much-needed melding of research and practice. Typically, however, they embody only the early ("alpha") stages of the design and refinement process” (Burkhardt and Schoenfeld, 2003: 4)
- See design-based research
2.2 A model for effective R<-->P
- Robust mechanisms for taking ideas from laboratory scale to widely used practice.
- Norms for research methods and reporting that are rigorous and consistent, resulting in a set of insights and/or prototype tools on which designers can rely. The goal, achieved in other fields, is cumulativity (p. 5)
- A reasonably stable theoretical base
- Teams of adequate size to grapple with large tasks, over the relatively long time scales required for sound work
- Sustained funding to support the R<-->P process on realistic time scales
- Individual and group accountability for ideas and products
Basically, we can summarise this as a call for more use-based research (top/right) in Pasteur's quadrant (Stokes, 1997).
|applied||Edison (invention)||Pasteur (both)|
|not applied||PhD students ;)||Bohr (pure theory)|
“Our point is that the same profitable dialectic between theory and practice can and should occur (with differing emphases on the R&D components) from the initial stages of design all the way through robust implementation on a large scale.” (Burkhardt and Schoenfeld, 2003: 5)
3 Linking Rigor with Relevance(Smith et al. 2013: 147)
Smith et al. (2013:152) reconceptualize Stokes quadrant in the following way:
| Quest for
|Yes|| Bohrs Quandrant (Knowledge)
Purpose: To systematically generate reliable and rigorous EPBs
Key Words: internal validity
| Pasteurs Quadrant (Use-Based)
Purpose: To merge "know what" (EBP) with "know how" (PBE)
Key Words: internal + external validity, collaboration, translation of research to practice
|No|| Unestablished Practices Quadrant (Speculation)
Purpose: To persuade without the need for objective data
Keywords: face validity, conjecture, anecdote, conventional wisdom
| Edison's Quadrant (Know-How)
Purpose: To generate and improve PBE within real world contexts
Key Words: exteranl validity, action research, data-driven, effectiveness
|Consideration of use?|
Unlike most other adaptations of Stokes' model, this model also conceptualizes the lower left quandrant: “This quadrant re- flects Galbraith’s (1958) concept of conventional wisdom—ideas or explanations that, though widely held, are not examined in any meaningful way and are therefore oftentimes inaccurate.” (Smith et al. 2013:152).
John R. Feussner, in a talk (retrieved Jan 2014), presented a more dynamic module that visualized the interplay between Stokes 3 types of research and understanding / technology.
- Barret, Angeline et al. (2007). Initiatives to improve the quality of teaching and learning. A review of recent literature. Background paper prepared for the Education for All Global Monitoring Report 2008 Eucation for All by 2015: will we make it?, Unesco, PDF from psu.edu
- Briars,D . (March, 2001). Mathematics performance in the Pittsburgh public schools. Presentation at a Mathematic Assessment Resource Service conferenceo on tools for systemic improvement, San Diego, CA.
- Briars, D, & Resnick,L . (2000). Standards, assessments-and what else? The essential elements of standards-based school improvement. Pittsburgh, PA: University of Pittsburgh.
- Burkhardt, H, Fraser, R., & Ridgway, J. (1990) The dynamics of curriculum change. In I. Wirszup& R. Streit (Eds.), Developments in school mathematics around the world, Vol.2 (pp. 3-30). Reston,VA: National Council of Teachers of Mathematics.
- Dillon, S. (2003, February6 ). Thousands of schools may run afoul of new law. New York Times. Retrieved September 12, 2003, from http://www.nytimes.com/2003/02/16/education/16EDUC.html
- Gardner, H. (1985). The mind's new science: A history of the cognitive revolution. New York: Basic Books.
- Burkhardt, Hugh and Alan H. Schoenfeld, Improving Educational Research: Toward a More Useful, More Influential, and Better-Funded Enterprise, Educational Researcher , Vol. 32, No. 9 (Dec., 2003), pp. 3-14 JStor
- Magidson, S. (2002). Teaching, research, and instructional design: Bridging communities in mathematics education. Dissertation Abstracts International 63/09, p. 3139. (UMI No. AAT 3063466)
- Pellegrino, J. W. (2001). Setting research agendas in science, mathematics, and technology education: The National Research Council’s How People Learn report. Proceedings of the Second AAAS Technology Education Research Conference. Retrieved from http://www.project2061.org/events/meetings/technology/tech2/Pellegrino.htm
- Senk, S. L., & Thompson, D. R. (Eds.). (2002). Standards-based school mathematics curricula: What are they? What do students learn? Mahwah, NJ: Erlbaum.
- Smith, Garnett J. , Matthew M. Schmidt, Patricia J. Edelen-Smith, Bryan G. Cook (2013). Pasteur's Quadrant as the Bridge Linking Rigor With Relevance, Exceptional Children, 79 (2). Abstract/PDF
- Stokes, D. (1997). Pasteur's Quadrant: Basic science and technological innovation. Washington, DC: Brookings Institution Press.
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