Kurzfassung
Experimentelle Unterrichtsforschung stellt besondere Anforderungen an die Versuchsplanung und Datenauswertung. Dazu stehen in der Literatur zahlreiche einschlägige Verfahren zur Verfügung. Sie sind für die experimentelle Unterrichtsforschung sogar speziell aufgearbeitet und exemplifiziert. Allerdings setzen die Verfahren im Allgemeinen relativ große Stichproben (N = large) voraus. Der folgende Artikel stellt einen Versuchsplan mit Messwiederholungen und das dazugehörige statistische Verfahren (Rank Order Tests) für eine experimentelle Unterrichtsforschung bereit, bei der die Fallselektion für kleine Stichproben (N = small) eine herausragende Rolle spielt. Rank Order Tests ermöglichen dabei eine adäquate statistische Auswertung, die zudem die Messung abhängiger Variablen (z.B. Lernzuwachs) auf Ordinalskalenniveau zulassen.
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Literatur
Berliner, D. C., & Calfee, R. (Eds.) (1996). Handbook of educational psychology. New York: Macmillan.
Blatter, J., & Haverland, M. (2012). Designing case studies: explanatory approaches in small-N Research. New York: Palgrave Macmillan.
Bredenkamp, J. (1974). Nonparametrische Prüfung von Wechselwirkungen. Psychologische Beiträge, 16, 398–416.
Brophy, J. E., & Good, T. L. (1986). Teacher behaviour and student achievement. In M. C. Wittrock (Ed.), Handbook of research on teaching (pp. 328–375). London: Macmillan.
Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models: applications and data analysis methods. Newbury Park, CA: Sage.
Cooper, M. (1988). Nonparametric statistics. In J. P. Keeves (Ed.), Educational research, methodology, and measurement: an international handbook (pp. 705–710). Oxford: Pergamon Press.
Cronbach, L. J., & Snow, R. E. (1977). Aptitudes and instructional methods: a handbook for research on aptitude-treatment interactions. New York: Irvington.
George, A. L., & Bennett, A. (2005). Case studies and theory development in the social sciences. Cambridge: MIT Press
Gerring, J. (2007). Case study research. Cambridge: University Press.
Gibbons, J. D., & Chakraborti, S. (2003). Nonparametric statistical inference. New York: Dekker.
Goodwin, L. D., & Goodwin, W. L. (1985). Statistical techniques in AERJ articles, 1979-193: The preparation of graduate students to read the educational research literature. Educational Researcher, 14(2), 5–11.
Graham, S., Harris, K.H., & Zito, J. (2005). Promoting internal and external validity: a synergism of laboratory-like experiments and classroom-based self-regulated strategy development research. In G.D. Phye, D.H. Robinson & J.R. Levin (Eds.), Empirical methods for evaluating educational environments (pp. 235–265). New York.
Hattie, J.C.A. (2009). Visible learning: A synthesis of 800+ meta analyses on achivement. New York: Routledge.
Hettmansperger, T. P. (1984). Statistical inference based on ranks. Malabar, Fl: Krieger.
Hox, J. J. (2000). Multilevel analysis of grouped and longitudinal data. In T. D. Little, K. U. Schnabel & J. Baumert (Eds.), Modeling longitudinal and multilevel data (pp. 15–32). London: Lawrence Erlbaum Associates.
Huck, S. W. (2009). Reading statistics. Boston: Pearson.
Kelly, A. E., & Lesh, R. (2000). Trends and shifts in research methods.. In A. E. Kelly & R. A. Lesh (Eds.), Handbook of Research design in mathematics and science education (pp. 35–44). London: Lawrence Erlbaum.
Keselman, H. J., Huberty, C. J., Lix, L. M., Olejnik, S., Cribbie, R. A., Donahue, B., Kowalchuk, R. K., Lowman, L. L., Petoskey, M. D., Keselman, J. C. & Levin, J. R. (1998). Statistical practices of educational researchers: An analysis of their ANOVA, MANOVA, and ANCOVA analyses. Review of Educational Research, 68, 350–386.
Kirk, R. E. (1995). Experimental Design (3rd Edition). Pacific Grove, CA: Brooks/Cole Publishing Company.
Klauer, K. J. (1973). Das Experiment in der pädagogischen Forschung. Düsseldorf: Schwann.
Klauer, K. J. (2005). Das Experiment in der pädagogisch-psychologischen Forschung (Reprint). Münster: Waxmann.
Krantz, D. H., Luce, R. D., Suppes, P. & Tversky, A. (1971). Foundations of Measurement (Vol. 1). New York: Academic Press.
Kvam, P. H., & Vidakovic, B. (2007). Nonparametric statistics with applications to science and engineering. New York: Wiley.
Leeuw, de J., & Meijer, E. (2008). Handbook of multilevel analysis (pp. 207–236). Berlin. Springer.
Lewis, D. G. (1968). Experimental design in education. London: University of London Press.
Lienert, G. A. (1978). Verteilungsfreie Methoden in der Biostatistik (Bd. II). Meisenheim am Glan: Hain.
Lix, L. M., Keselman, J. C, & Keselman, H. J. (1996). Consequences of assumption violations revisited: a quantitative review of alternatives to the one-way analysis of variance F test. Review of Educational Research, 66, 579–620.
Marjoribanks, K. M. (1988). Interaction effects. In J. P. Keeves, Educational research, methodology, and measurement: an international handbook (pp. 625-628). Oxford: Pergamon Press. Namboodiri, N. K. (1972). Experimental design in which each subject is used repeatedly. Psychological Bulletin, 77(1), 54–64.
Narens, L. (2007). Introduction to the Theories of Measurement and Meaningfulness and the Use of Symmetry in Science. London: Lawrence Erlbaum Associates.
O´Malley, P. M. (1988). Detection of interaction. In J. P. Keeves, Educational research, methodology, and measurement: an international handbook (pp. 625–628). Oxford: Pergamon Press.
Pett, M. A. (1997). Nonparametric statistics for health care research. London: Sage.
Ragin, C. C. (2004). Turning the tables: how case-oriented research challenges variable-oriented research.. In H. E. Brady and D. Collier (Eds.), Rethinking social inquiry (pp. 123–138). Lanham: Rowman & Littlefield.
Raudenbush, S. W. (2008). Many small groups. In J. de Leeuw & E. Meijer (Eds.), Handbook of multilevel analysis (pp. 207–236). Berlin. Springer.
Roberts, F. S. (1979). Measurement theory with applications to decisionmaking, utility, and the social sciences. London: Addison Wesley.
Savage, I. R. (1951). Contributions to the theory of rank order statistics-the “trend” case. Technical report No.5, Department of Statistics, Stanford, Stanford University.
Siegel, S. (1956). Nonparametric statistics for the behavioral sciences. New York: McGraw-Hill.
Siegel, S., & Castellan, N. J. (1988). Nonparametric statistics. New York: McGraw-Hill.
West, C. K., Carmody, C., & Stallings, W. M. (1983). The quality of research articles in the Journal of Educational Researcher, 25, 26–30.
Winer, B. J. (1971). Statistical principles in experimental design. New York: Wiley.
Zendler, A., & Pfeiffer, T. (2009). Methodische Befunde zu durchgeführten Unterrichtsexperimenten. Empirische Pädagogik, 23(2), 208–221.
Zendler, A., Vogel, M., & Spannagel, C. (2012). Useful experimental designs in educational research. International Journal of Research Studies in Education, 2(2), 83–106.
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Zendler, A. (2014). Experimentelle Unterrichtsforschung in der Mathematik mit kleinen Stichproben: Rank Order Test und Versuchsplan mit Messwiederholungen. In: Sproesser, U., Wessolowski, S., Wörn, C. (eds) Daten, Zufall und der Rest der Welt. Springer Spektrum, Wiesbaden. https://doi.org/10.1007/978-3-658-04669-9_25
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