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A Modeling and Simulation Approach to Informal Inference: Successes and Challenges

  • Jennifer NollEmail author
  • Mulugeta Gebresenbet
  • Erin Demorest Glover
Chapter

Abstract

The research presented explores various ways in which introductory statistics students used dynamic statistical software to generate models and simulations as tools to support their thinking and to help them answer informal statistical inference questions. Modern computing technology has changed the nature of statistics as a discipline. Introductory statistics courses need to change if they are to keep pace with modern innovations in statistics. This research report focuses on 16 students enrolled in an elementary statistics course. The course implemented CATALST curricula and the extensive use of TinkerPlots™ software in order to investigate students’ successes and challenges as they engaged with the technology as a tool for answering informal statistical inference questions.

Keywords

Statistics Informal inference Technology Simulation TinkerPlots™ 

References

  1. Ben-Zvi, D., & Friedlander, A. (1997). Statistical thinking in a technological environment. In J. B. Garfield, & G. Burrill (Eds.), Research on the role of technology in teaching and learning statistics. Proceedings of the 1996 IASE Round Table Conference (pp. 45–55). University of Granada, Spain, 23–27 July, 1996. International Statistical Institute Voorburg, The Netherlands.Google Scholar
  2. Chance, B., Ben-Zvi, D., Garfield, J., & Medina, E. (2007). The role of technology in improving student learning of statistics. Technology Innovations in Teaching Statistics, 1(1), Retrieved from http://escholarship.org
  3. Chance, B., delMas, R., & Garfield, J. (2004). Reasoning about sampling distributions. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning, and thinking (pp. 295–323). Dordrecht, The Netherlands: Kluwer.CrossRefGoogle Scholar
  4. Cobb, G. W. (2007). The introductory statistics course: A Ptolemaic curriculum? Technology Innovations in Statistics Education, 1(1). Retrieved from http://escholarship.org
  5. Fitzallen, N., & Watson, J. (2010). Developing statistical reasoning facilitated by TinkerPlots. In C. Reading (Ed.), Data and context in statistics education: Towards an evidence-based society. Proceedings of the Eighth International Conference on Teaching Statistics (ICOTS8, July, 2010), Ljublijana, Slovenia. Voorburg, The Netherlands: International Statistical Institute.Google Scholar
  6. Garfield, J. B., & Ben-Zvi, D. (2009). Developing students’ statistical reasoning: Connecting research and teaching practice. New York: Springer.Google Scholar
  7. Garfield, J., delMas, B., & Zieffler, A. (2012). Developing statistical modelers and thinkers in an introductory, tertiary-level statistics course. ZDM Mathematics Education, 44, 883–898.CrossRefGoogle Scholar
  8. Lesh, R., et al. (2000). Principles for developing thought revealing activities for students and teachers. In A. Kelly & R. Lesh (Eds.), Handbook of research design in mathematics and science education. Mahweh, New Jersey: Lawrence Erlbaum Associates.Google Scholar
  9. Maxara, C., & Biehler, R. (2006). Students’ probabilistic simulation and modelling competence after a computer-intensive elementary course in statistics and probability. In A. Rossman, & B. Chance (Eds.), Working cooperatively in statistics education. Proceedings of the Seventh International Conference on Teaching Statistics (ICOTS7, July 2006), Salvador, Brazil. Voorburg, The Netherlands: International Statistical Institute.Google Scholar
  10. Morgan, K. L. (2011). Using simulation methods to introduce inference. Consortium for the Advancement of Undergraduate Statistics Education (CAUSE) webinar. Retrieved from http://www.causeweb.org/webinar/teaching/
  11. Nolan, D., & Lang, D. T. (2010). Computing in the statistics curricula. The American Statistician, 64(2), 97–107.CrossRefGoogle Scholar
  12. Rubin, A., Bruce, B., & Tenney, Y. (1991). Learning about sampling: Trouble at the core of statistics. In D. Vere-Jones (Ed.), Proceedings of the Third International Conference on Teaching Statistics (Vol. 1, pp. 314–319). Voorburg, The Netherlands: International Statistical Institute.Google Scholar
  13. Saldanha, L., & Thompson, P. (2003). Conceptions of sample and their relationship to statistical inference. Educational Studies in Mathematics, 51, 257–270.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jennifer Noll
    • 1
    Email author
  • Mulugeta Gebresenbet
    • 2
  • Erin Demorest Glover
    • 1
  1. 1.Portland State UniversityPortlandUSA
  2. 2.Addis Abeba UniversityAddis AbabaEthiopia

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