Dynamic, Interactive Documents for Teaching Statistical Practice (original) (raw)
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… of the Fifth International Conference on …, 1998
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Dynamic interactive technology brings new opportunities for helping students learn central statistical concepts. Research and classroom experience can be help identify concepts with which students struggle, and an "action-consequence" pre-made technology document can engage students in exploring these concepts. With the right questions, students can begin to make connections among their background in mathematics, foundational ideas that undergrid statistics and the relationship these ideas. The ultimate goal is to have students think deeply about simple and basic statistical ideas so they can see how they lead to reasoning and sense making about data and about making decisions about characteristics of a population from a sample.Technology has a critical role in teaching and learning statistics, enabling students to use real data in investigations, to model complex situations based on data, to visualize relationships using different representations, to move beyond calculations to interpreting statistical processes such as confidence intervals and correlation, and to generate simulations to investigate a variety of problems including laying a foundation for inference. Thus, graphing calculators, spreadsheets, and interactive dynamic software can all be thought of as tools for statistical sense making in the service of developing understanding. NEW OPPORTUNITIES Dynamic interactive technology has the potential to extend this tool to help students understand central statistical concepts. The ability to link representations, where changes in one representation are reflected in the others, enables students to take an action, immediately see the consequences and reflect on the meaning of these consequences to make sense of the statistics-an action-consequence principle (Dick & Burrill, 2006). To maximize this potential and allow students to explore statistical concepts in deeper ways, it is possible to impose constraints on what they can do, in essence creating action-consequence "microworlds" in which students can play with a statistical concept in a variety of ways but where the opportunity to go astray, both mathematically and operationally, is limited. An action-consequence document is similar to an applet (e.g
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The Internet offers a huge array of teaching resources for statistics. Here we present a selection of engaging Web-based tools, ranging from class surveys to individual simulation experiments. Abstract: The surprising property of many data sets that their first significant digits follow Benford's Law provides examples that can pique and hold students' interest. Several ideas for student activities are presented. Abstract: Computational formulae are a throwback to a time when computers were not widely available. Today their teaching obscures important underpinnings of statistical theory and practice. Journal of Statistics Education, v17n2: Abstract: The use of the Internet as a teaching tool continues to grow in popularity at colleges and universities. We consider, from the students' perspective, the use of an Internet approach compared to a lecture and lab-based approach for teaching an introductory course in statistical methods. We conducted a survey of introductory statistics students. Contradictory to what was hypothesized by the authors, they favored keeping the lecture and lab-based approach for teaching the class. Abstract: This study examined students' development of reasoning about quantitative bivariate data during a onesemester university-level introductory statistics course. There were three research questions of interest: (1) What is the nature, or pattern of change in students' development in reasoning throughout the course?;
Enhancing statistical literacy
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Current secondary school statistics curricula focus on procedural knowledge and pay too little attention to statistical reasoning. As a result, students are not able to apply their knowledge to practice. In addition, education often targets the average student, which may lead to gifted students missing challenge. This study explored ways to enhance grade 8 (Pre-University level) students’ statistical literacy through within-class differentiation. The developed course materials consisted of a differentiated module in the Digital Mathematics Environment (DME), combined with investigation activities during classroom sessions. The material focused on statistical reasoning using visual representations made with TinkerPlots. We concluded that this teaching arrangement indeed increased students’ statistical literacy.
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This paper provides a broad overview of the role technological tools can play in helping students understand and reason about important statistical ideas. We summarize recent developments in the use of technology in teaching statistics in light of changes in course content, pedagogical methods, and instructional formats. Issues and practical challenges in selecting and implementing technological tools are presented discussed, and examples of exemplary tools are provided along with suggestions for their use.
The Royal Statistical Society Centre For Statistical Education
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Teaching & Learning Statistical Literacy
This is being shared under a Creative Commons Attribution-NonCommercial-NoDerivs (BY-NC-ND) license. These are annotated slides from an invited talk at the UCI Department of Statistics in February 2018. A 2017 paper (https://www.mdpi.com/2227-7102/7/1/3) outlined a new, developmental, model of statistical literacy that reflects the complexity of reasoning and habits of mind that practicing scientists, and those who work with data for a living, need to cultivate in order to recognize, choose, and interpret statistical methods. While automated analyses can exploit massive amounts of data, the interpretation—and, possibly more importantly, the replication—of results are challenging without adequate statistical literacy. Also, some areas of science, and scientific publishing more generally, are struggling with insufficient/inappropriate statistical reasoning in writing, reviewing, and editing. Statistical literacy that is sufficient for professional use of data for decision making or argumentation goes beyond "knowing statistics" (i.e., choosing the right method given a data type or question). It involves nine areas of knowledge, skill, and ability (KSAs). This talk will present these KSAs and emphasize how their development can be encouraged and documented, with attention to scaling some of the KSAs over time, integrating them into existing courses, and how the KSAs can be grown and purposefully developed for undergraduate and graduate students in and outside of the discipline of statistics and data science. Here is the link to include for this 2017 paper (open source): http://www.mdpi.com/2227-7102/7/1/3
In the 21st century, schools have been increasingly expected to raise students prepared for a world of quantities and uncertainty. As statistical practices become an important skill for every individual, researchers and educators work on ways to translate the methodologies of professional statisticians in the teaching and learning environments. Technological tools are helpful in translating statistical investigations into the classroom. The purpose of our research is to understand teachers’ experiences about integrating statistical practices into their STEM lesson plans by using LabStar, a dynamic data collection and data analysis tool. Findings were investigated under four categories: personal development, in-class implementation, views about the mobile application and the tool, and statistical investigation environment. Future research was recommended to investigate teachers’ professional development opportunities to integrate meaningful statistical practices in their lesson plans.