Abstract
Quantitative data from the main study are summarized and analyzed. Both the structure and modeling workshops generated statistically significant performance gains. Thus, after students had participated in both the workshops, their performances on both parts of the Algebra Test—that is to say, on the questions concerning structure and on the questions concerning modeling—were much improved. Cohen’s d effect sizes for each set of workshops (the structure workshops and the modeling workshops) were large. The chapter concludes by introducing two questions. First, although the performance gains were highly statistically significant, and the effect sizes large, were they educationally significant? And, second, “What was there about the interventions which generated such apparently impressive results?”
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References
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
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Kanbir, S., Clements, M.A.(., Ellerton, N.F. (2018). Quantitative Analyses of Data. In: Using Design Research and History to Tackle a Fundamental Problem with School Algebra. History of Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-319-59204-6_7
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DOI: https://doi.org/10.1007/978-3-319-59204-6_7
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