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Abstract
Educational innovations often involve intact subgroups, such as school classes or university departments. In small-scale educational evaluation research, typically involving 1 to 20 subgroups, differences among these subgroups are often neglected. This article presents a mixed method from a qualitative perspective, in which differences among intact subgroups regarding one construct or effect are first quantitatively identified and subsequently qualitatively described and explained by differences among the contexts of the separate intact subgroups. Its focus on the contexts of intact subgroups, where organizational factors can be modified, makes this method interesting from a management perspective. In evaluations, repeated application of the method deserves a place beside other analytical methods.
Keywords mixed methods, multilevel mixed design, intact groups, education, evaluation
References
Section:
|
Babbie, E. (2012). The practice of social research (13th ed.). Belmont, CA: Thomson Wadsworth. Google Scholar | |
|
Bamberger, M., Rao, V., Woolcock, M. (2010). Using mixed methods in monitoring and evaluation: Experiences from international development. In Tashakkori, A., Teddlie, C. (Eds.), SAGE handbook of mixed methods in social & behavioral research (2nd ed., pp. 613-641). Thousand Oaks, CA: Sage. Google Scholar | Crossref | |
|
Becker, H. S. (1992). Cases, causes, conjunctures, stories, and imagery. In Ragin, C. C., Becker, H. S. (Eds.), What is a case? Exploring the foundations of social inquiry (pp. 205-216). Cambridge, England: Cambridge University Press. Google Scholar | |
|
Bickel, R. (2007). Multilevel analysis for applied research: It’s just regression! New York, NY: Guilford Press. Google Scholar | |
|
Campbell, D. T., Stanley, J. C. (1963). Experimental and quasi-experimental designs for research. Chicago, IL: Rand McNally. Google Scholar | |
|
Cohen, J., Cohen, P., West, S. G., Aiken, L. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum. Google Scholar | |
|
Collins, K. M. T. (2010). Advanced sampling designs in mixed research: Current practices and emerging trends in the social and behavioral sciences. In Tashakkori, A., Teddlie, C. (Eds.), SAGE handbook of mixed methods in social & behavioral research (2nd ed., pp. 353-377). Thousand Oaks, CA: Sage. Google Scholar | Crossref | |
|
Games, P. A. (1976). Limitations of analysis of covariance on intact group quasi-experimental designs. Journal of Experimental Education, 44(4), 51-54. Google Scholar | Crossref | ISI | |
|
Gibson, J. J. (1979). The ecological approach to visual perception. Boston, MA: Houghton Mifflin. Google Scholar | |
|
Greene, J. C. (2007). Mixed methods in social inquiry. San Francisco, CA: Jossey-Bass. Google Scholar | |
|
Hox, J. J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). New York, NY: Routledge. Google Scholar | |
|
Ivankova, N. V. (2013). Implementing quality criteria in designing and conducting a sequential QUAN → QUAL mixed methods study of student engagement with learning applied research methods online. Journal of Mixed Methods Research, 8(1), 25-51. doi:10.1177/1558689813487945 Google Scholar | SAGE Journals | ISI | |
|
Kaul Nastasi, B., Hitchcock, J. H., Brown, L. M. (2010). An inclusive framework for conceptualizing mixed methods design typologies. In Tashakkori, A., Teddlie, C. (Eds.), Sage handbook of mixed methods in social & behavioral research (2nd ed., pp. 305-338). Thousand Oaks, CA: Sage. Google Scholar | Crossref | |
|
Lincoln, Y. S. (2010). “What a long, strange trip it’s been . . .”: Twenty-five years of qualitative and new paradigm research. Qualitative Inquiry, 16, 3-9. doi:10.1177/1077800409349754 Google Scholar | SAGE Journals | ISI | |
|
Lincoln, Y. S., Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage. Google Scholar | |
|
Lord, F. M. (1967). A paradox in the interpretation of group comparisons. Psychological Bulletin, 68, 304-305. doi:10.1037/h0025105 Google Scholar | Crossref | Medline | ISI | |
|
Maxwell, J. A. (1992). Understanding and validity in qualitative research. Harvard Educational Review, 62, 279-301. Google Scholar | Crossref | ISI | |
|
Maxwell, J. A. (2013). Qualitative research design: An interactive approach (3rd ed.). Thousand Oaks, CA: Sage. Google Scholar | |
|
Maxwell, J. A., Mittapalli, K. (2010). Realism as a stance for mixed methods research. In Tashakkori, A., Teddlie, C. (Eds.), SAGE handbook of mixed methods in social & behavioral research (2nd ed., pp. 145-167). Thousand Oaks, CA: Sage. Google Scholar | Crossref | |
|
McNeil, K. A., Newman, I., Kelly, F. J. (1996). Testing research hypotheses with the general linear model. Carbondale: Southern Illinois Press. Google Scholar | |
|
Mohr, L. B. (1982). Explaining organizational behavior. San Francisco, CA: Jossey-Bass. Google Scholar | |
|
Morse, J. M. (2003). Principles of mixed methods and multimethod research design. In Tashakkori, A., Teddlie, C. (Eds.), Handbook of mixed methods in social and behavioral research (pp. 189-208). Thousand Oaks, CA: Sage. Google Scholar | |
|
Morse, J. M., Niehaus, L. (2009). Mixed method design: Principles and procedures. Walnut Creek, CA: Left Coast Press. Google Scholar | |
|
Murnane, R. J., Willett, J. B. (2011). Methods matter: Improving causal inference in educational and social science research. New York, NY: Oxford University Press. Google Scholar | |
|
Newman, D., Newman, I., Salzman, J. (2010). Comparing OLS and HLM models and the questions they answer: Potential concerns for type VI errors. Multiple Linear Regression Viewpoints, 36(1), 1-9. Google Scholar | |
|
Newman, I., Fraas, J. W., Newman, C., Brown, R. (2002). Research practices that produce type VI errors. Journal of Research in Education, 12(1), 138-145. Google Scholar | |
|
Norman, D. A. (1990). The design of everyday things. New York, NY: Doubleday. Google Scholar | |
|
Onwuegbuzie, A. J., Johnson, R. B. (2006). The validity issue in mixed research. Research in the Schools, 13(1), 48-63. Google Scholar | |
|
Onwuegbuzie, A. J., Johnson, R. B., Collins, K. M. T. (2011). Assessing legitimation in mixed research: A new framework. Quality & Quantity, 45, 1253-1271. doi:10.1007/s11135-009-9289-9 Google Scholar | Crossref | ISI | |
|
Pawson, R. (2008). Method mix, technical hex, theory fix. In Bergman, M. M. (Ed.), Advances in mixed methods research: Theories and applications (pp. 120-137). Thousand, Oaks, CA: Sage. Google Scholar | |
|
Pawson, R., Tilley, N. (1997). Realistic evaluation. London, England: Sage. Google Scholar | |
|
Rabe-Hesketh, S., Skrondal, A. (2008). Multilevel and longitudinal modeling using Stata (2nd ed.). College Station, TX: Stata Press. Google Scholar | |
|
Sammons, P. (1996). Complexities in the judgement of school effectiveness. Educational Research and Evaluation, 2, 113-149. doi:10.1080/1380361960020201 Google Scholar | Crossref | |
|
Sammons, P. (2010). The contribution of mixed methods to recent research on educational effectiveness. In Tashakkori, A., Teddlie, C. (Eds.), SAGE handbook of mixed methods in social & behavioral research (2nd ed., pp. 697-723). Thousand Oaks, CA: Sage. Google Scholar | Crossref | |
|
Sandelowski, M. (2003). Tables or tableaux? The challenges of writing and reading mixed methods studies. In Tashakkori, A., Teddlie, C. (Eds.), Handbook of mixed methods in social & behavioral research (pp. 321-350). Thousand Oaks, CA: Sage. Google Scholar | |
|
Shadish, W. R., Cook, T. D., Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin. Google Scholar | |
|
Snijders, T. A. B., Bosker, R. J. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. London, England: Sage. Google Scholar | |
|
Teddlie, C. B., Tashakkori, A. (2009). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences. Thousand Oaks, CA: Sage. Google Scholar | |
|
Teddlie, C. B., Tashakkori, A. (2010). Overview of contemporary issues in mixed methods research. In Tashakkori, A., Teddlie, C. (Eds.), Sage handbook of mixed methods in social & behavioral research (2nd ed., pp. 1-41). Thousand Oaks, CA: Sage. Google Scholar | Crossref | |
|
West, B., Welch, K. B., Galecki, A. T. (2007). Linear mixed models: A practical guide using statistical software. Boca Raton, FL: Chapman & Hall. Google Scholar | |
|
Yin, R. K. (2009). Case study research: Design and methods (4th ed.). Thousand Oaks, CA: Sage. Google Scholar |
