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Members of CATALST meet several times each year to discuss research articles in statistics education.
Current Reading for March , 2009
Clements, D. H. (2007). Curriculum Research: Toward a Framework for “Research-based Curricula”. Journal for Research in Mathematics Education, 38(1), 35–70.
Some articles that we have discussed in the past are:
Aberson, C. L., Berger, D. E., Healy, M. R., Kyle, D. J. & Romero, V. L. (2000). Evaluation of an interactive turotiral for eaching the centeral limit theorem. Teaching Statistics, 27, 289-291.
Alldredge, J. R. & Brown, G. R. (2006). Association of course performance with student beliefs: An analysis by gender and instructional software environment. Statistics Education Research Journal, 5(1), 64-77. http://www.stat.auckland.ac.nz/~iase/serj/SERJ_5(1)_Alldredge_Brown.pdf
Cooper, L. L. & Shore, F. S. (2008). Students’ Misconceptions in Interpreting Center and Variability of Data Represented via Histograms and Stem-and-leaf Plots. Journal of Statistics Education, 16(2). http://www.amstat.org/publications/jse/v16n2/cooper.html
Dunbar, K. N., Fugelsang, J. A. & Stein, C. (2007). Do naive therories ever go away? Using brain and behavior to understand changes in concepts. In M. Lovett and P. Shah (Eds.), Thinking with Data (Proceedings of the 33rd Carnegie Symposium on Cognition) (pp. 193-205). New York: Erlbaum.
Eichler, A. (2006). Individual curricula: Beliefs behind teachers' beliefs. Proceedings of the Seventh International Conference on Teaching Statistics, Salvador, Bahia, Brazil. http://www.stat.auckland.ac.nz/~iase/publications/17/6G4_EICH.pdf
Froelich, A. G., Stephenson, W. R., & Duckworth, W. M. (2008). Assessment of Materials for Engaging Students in Statistical Discovery. Journal of Statistics Education, 16(2). http://www.amstat.org/publications/jse/v16n2/froelich.html
Groth, R. E. (2005). An investigation of statistical thinking in two different contexts: Detecting a signal in a noisy process and determining a typical value. The Journal of Mathematical Behavior, 24(2), 109-124.
Konold, C. & Kazak, S. (2008). Reconnecting data and chance. Technology Innovations in Statistics Education, 2(1), Article 1. http://repositories.cdlib.org/uclastat/cts/tise/vol2/iss1/art1
Lehrer, R. & Schauble, L. (2007). Contrasting emerging conceptions of distribution in contexts of error and natural variation. In M. Lovett and P. Shah (Eds.), Thinking with Data (Proceedings of the 33rd Carnegie Symposium on Cognition) (pp. 149-176). New York: Erlbaum.
Lesh, R., Caylor, E., Gupta, S. (2007). Data modeling & the infrastructural nature of conceptual tools. International Journal of Computers for Mathematical Learning, 12(3), 231–254. http://www.springerlink.com/content/j416127135xt3654/fulltext.pdf
Meyer, O. & Lovett, M. (2002). Implementing a computerized tutor in a
Quilici, J. L., & Mayer, R. E. (2002). Teaching students to recoginze structural similarities between statistics word problems.Applied Cognitive Psychology, 16, 325-342.
Schwartz, D., Sears, D. & Chang, J. (2007). Reconsidering prior knowledge. In M. Lovett and P. Shah (Eds.), Thinking with Data (Proceedings of the 33rd Carnegie Symposium on Cognition) (pp. 319-344). New York: Erlbaum.
Sedlmeier, P. & Gigerenzer, G. (1997). Intuitions about sample size: The empriical law of large numbers. Journal of Behavioral Decision Making, 10, 33-51.
Sorto, M. . & White, A. (2008). The Gumball Machine: Linking Research and Practice About the Concept of Variability. Journal of Statistics Education, 16(2). http://www.amstat.org/publications/jse/v16n2/white.html
Speer, N. M. (2005). Issues of methods and theory in the study of mathematics teachers' professed and attributed beliefs. Educational Studies in Mathematics 58, 361–391.
Thompson, P. W., Liu, Y. & Saldanha, L. A. (2007). Intricacies of statistical inference and teachers' understandings of them. In M. Lovett and P. Shah (Eds.), Thinking with Data (Proceedings of the 33rd Carnegie Symposium on Cognition) (pp. 207-231). New York: Erlbaum.
