Technology for enhancing statistical reasoning at the school level The purpose of this chapter is to provide an updated overview of digital technologies relevant to statistics education, and to summarize what is currently known about how these new technologies can support the development of students’ statistical reasoning at the school level. A brief literature review of trends in statistics education is followed by a section on the history of technologies in statistics and statistics education. Next, an overview of various types of technological tools highlights their benefits, purposes and limitations for developing students’ statistical reasoning. We further discuss different learning environments that capitalize on these tools with examples from research and practice. Dynamic data analysis software applications for secondary students such as Fathom and TinkerPlots are discussed in detail. Examples are provided to illustrate innovative uses of technology. In the future, these uses may also be supported by a wider range of new tools still to be developed. To summarize some of the findings, the role of digital technologies in statistical reasoning is metaphorically compared with travelling between data and conclusions, where these tools represent fast modes of transport. Finally, we suggest future directions for technology in research and practice of developing students’ statistical reasoning in technology-enhanced learning environments.

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References in zbMATH (referenced in 16 articles , 1 standard article )

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  1. Ben-Zvi, Dani (ed.); Bakker, Arthur (ed.); Makar, Katie (ed.): Learning to reason from samples (2015) MathEduc
  2. Garfield, Joan; Le, Laura; Zieffler, Andrew; Ben-Zvi, Dani: Developing students’ reasoning about samples and sampling variability as a path to expert statistical thinking (2015) MathEduc
  3. Hesse, Daniela: How data get into the box. Analysing data with Fathom software using the example of box plots (2015) MathEduc
  4. Kuzle, Ana; Biehler, Rolf: Examining mathematics mentor teachers’ practices in professional development courses on teaching data analysis: implications for mentor teachers’ programs (2015) MathEduc
  5. Hofmann, Tobias; Maxara, Carmen; Meyfarth, Thorsten; Prömmel, Andreas: Using the software Fathom for learning and teaching statistics in Germany -- a review on the research activities of Rolf Biehler’s working group over the past ten years (2014) MathEduc
  6. Makar, Katie; Confrey, Jere: Wondering, wandering or unwavering? Learners’ statistical investigations with Fathom (2014) MathEduc
  7. Biehler, Rolf; Ben-Zvi, Dani; Bakker, Arthur; Makar, Katie: Technology for enhancing statistical reasoning at the school level (2013) MathEduc
  8. Ben-Zvi, Dani; Aridor, Keren; Makar, Katie; Bakker, Arthur: Students’ emergent articulations of uncertainty while making informal statistical inferences (2012) MathEduc
  9. Biehler, Rolf; Pratt, Dave: Research on the reasoning, teaching and learning of probability and uncertainty (2012) MathEduc
  10. Landín, Pedro R.; Sánchez, Ernesto: Levels of probabilistic reasoning of high-school students facing binomial distribution problems (2010) MathEduc
  11. Shafer, Kathryn: Scrambling data with fathom to simulate the hypothesis (2010) MathEduc
  12. Mathews, Susann M.; Reed, Michelle K.: Using Fathom to solve the high dive problem (2008) MathEduc
  13. Meyfarth, Thorsten: Conception, implementation, and analysis of a simulation intensive start into stochastics in upper secondary. An explorative development study. (2008)
  14. Prömmel, Andreas; Biehler, Rolf: Introduction to stochastics at lower secondary level with simulations using the software tool FATHOM (2008) MathEduc
  15. Wanko, Jeffrey J.: Exploring the cereal box problem with Fathom (2008) MathEduc
  16. Moyer, Todd O.: Simulating basketball free throws using Fathom (2007) MathEduc