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Marina Goodman

Bridge the digital divide by teaching students a useful technological skill while enhancing mathematics instruction focused on real-life matrix applications.

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Hamilton L. Hardison and Hwa Young Lee

In this article, we discuss funky protractor tasks, which we designed to provide opportunities for students to reason about protractors and angle measure. We address how we have implemented these tasks, as well as how students have engaged with them.

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Anne Quinn

The paper discusses technology that can help students master four triangle centers -- circumcenter, incenter, orthocenter, and centroid. The technologies are a collection of web-based apps and dynamic geometry software. Through use of these technologies, multiple examples can be considered, which can lead students to generalizations about triangle centers.

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Readers comment on published articles or offer their own ideas.

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Michael Dempsey

When understood and applied appropriately, mathematics is both beautiful and powerful. As a result, students are sometimes tempted to extend that power beyond appropriate limits. In teaching statistics at both the high school and college level, I have found that one of students' biggest struggles is applying their understanding of probability to make appropriate inferences.

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Nicole R. Juersivich

By using technology, students can conduct an experiment that quickly simulates a large number of random events. Much research has been done on students' conceptions and reasoning about probability (Jones et al. 2007). Recommendations for teaching probability have included just such use of concrete and digital manipulatives to simulate events as well as students' reflection on their initial predictions and analysis of their experiments and their results (NCTM 2000; Van de Walle et al. 2010). In fact, by using Excel® and Visual Basic to simulate coin flipping, students have been able to capitalize on these technological benefits to investigate, conceptualize, and refine their understanding of the law of large numbers.

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James R. Kett

The author uses Autograph, a powerful software program, to illustrate sampling distributions and to demonstrate the central limit theorem.