Title of Oral/Poster Presentation

Making Statistics Matter: Using Fitbit Activity Trackers to Enhance Undergraduate Statistics Instruction

Presenter Information

Jeffrey ThayneFollow
Victor LeeFollow

Class

Article

Department

Instructional Technology and Learning Sciences

Faculty Mentor

Victor Lee

Presentation Type

Oral Presentation

Abstract

For decades, researchers have consistently demonstrated that statistics learners struggle to understand the mean and what it represents, and despite many proposals to improve statistics instruction, these struggles continue today. Some have proposed that statistics learners use personally-relevant, self-collected data in the context of student-led data-inquiry, and have argued that that this may help learners deepen their understanding of the statistical concepts. A new class of technologies - physical activity data (PAD) devices - promises to afford statistics learners with precisely this kind of data and may thereby enhance statistics learning. In this study, three undergraduate learners were invited to wear a Fitbit One activity tracker for a week and a half, prior to participating in a study group session in which they explored their data using data visualization software. The study produced evidence that there were important statistical realizations made by the participants that were uniquely enabled by the use of self-data in the learning process, and that participants felt that the use of self-data enhanced the learning experience. Further, there were hints during the learning activities and interviews that the advantages to using large, messy, real, and personally relevant data sets predicted by previous research were at least partially realized by using Fitbit activity trackers.

Start Date

4-9-2015 1:00 PM

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Apr 9th, 1:00 PM

Making Statistics Matter: Using Fitbit Activity Trackers to Enhance Undergraduate Statistics Instruction

For decades, researchers have consistently demonstrated that statistics learners struggle to understand the mean and what it represents, and despite many proposals to improve statistics instruction, these struggles continue today. Some have proposed that statistics learners use personally-relevant, self-collected data in the context of student-led data-inquiry, and have argued that that this may help learners deepen their understanding of the statistical concepts. A new class of technologies - physical activity data (PAD) devices - promises to afford statistics learners with precisely this kind of data and may thereby enhance statistics learning. In this study, three undergraduate learners were invited to wear a Fitbit One activity tracker for a week and a half, prior to participating in a study group session in which they explored their data using data visualization software. The study produced evidence that there were important statistical realizations made by the participants that were uniquely enabled by the use of self-data in the learning process, and that participants felt that the use of self-data enhanced the learning experience. Further, there were hints during the learning activities and interviews that the advantages to using large, messy, real, and personally relevant data sets predicted by previous research were at least partially realized by using Fitbit activity trackers.