Students’ use of narrative when constructing statistical models in TinkerPlots
- 116 Downloads
Initial research has shown that simulating data from models created with computer software may enhance students’ understanding of concepts in introductory statistics; yet, there is little research investigating students’ development of statistical models. The research presented here examines small groups of students as they develop a model for a situation where a music teacher plays ten notes for a student who tries to guess each of the notes correctly. As students constructed their models and described their thinking, their descriptions were narrative in nature, focusing on the story of notes played and guessed. In this context, their focus on narrative appeared to support the development of productive statistical models. In addition, when students investigated pre-built TinkerPlots models, they preferred models that they perceived as more communicative or narrative in nature. These results have important pedagogical implications in terms of designing modeling curriculum.
KeywordsStatistics education Modeling Simulation Narrative TinkerPlots
The authors gratefully acknowledge the support of National Science Foundation for this CAREER project (NSF REC 1453822). Any conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. We also wish to thank Andee Rubin for thoughtful feedback on students’ use of narrative.
- Bruner, J. (1990). Acts of meaning. Cambridge: Harvard University Press.Google Scholar
- Cobb, G. W. (2007). The introductory statistics course: A Ptolemaic curriculum? Technology Innovations in Statistics Education, 1(1). http://escholarship.org/uc/item/6hb3k0nz.
- Doerr, H. M., delMas, R., & Makar, K. (2017). A modeling approach to the development of students’ informal inferential reasoning. Statistics Education Research Journal, 16(2), 86–115.Google Scholar
- Doerr, H. M., & Pratt, D. (2008). The learning of mathematics and mathematical modeling. In M.K. Heid & G. W. Blume (Eds.), Research on technology and the teaching and learning of mathematics: Research syntheses (pp. 259–285). Charlotte: Information Age Publishing.Google Scholar
- Fisher, W. R. (1987). Human communication as narration: Toward a philosophy of reason, value, and action. Columbia: University of South Carolina Press.Google Scholar
- Konold, C., & Lehrer, R. (2008). Technology and mathematics education: An essay in honor of Jim Kaput. In L. D. English (Ed.), Handbook of international research in mathematics education (2nd edn., pp. 49–72). Philadelphia: Taylor & Francis.Google Scholar
- Konold, C., & Miller, C. (2011). TinkerPlots™ Version 2.3 [Computer Software]. Amherst: Learn Troop.Google Scholar
- Laina, V., & Wilkerson, M. (2017). Modeling data by visualizing it. Proceedings of the 10th of the international forum for statistical reasoning, thinking and literacy, Rotorua.Google Scholar
- Lehrer, R. (2017). Modeling signal-noise processes supports student construction of a hierarchical image of sample. Statistics Education Research Journal, 16(2), 64–85.Google Scholar
- Noll, J., & Kirin, D. (2016). Student approaches to constructing statistical models using TinkerPlots™. Technology Innovations in Statistics Education, 9(1). http://escholarship.org/uc/item/05b643r9.
- Pfannkuch, M., Budgett, S., Fewster, R., Fitch, M., Pattenwise, S., Wild, C., & Ziedins, I. (2016). Probability modeling and thinking: What can we learn from practice? Statistics Education Research Journal, 15(2), 11–37.Google Scholar
- Wild, C. J., & Pfannkuch, M. (1999). Statistical thinking in empirical enquiry. International Statistical Review, 67(3), 223–248. https://doi.org/10.1111/j.1751-5823.1999.tb00442.x.CrossRefGoogle Scholar