Date of Award:

2016

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Instructional Technology and Learning Sciences

Advisor/Chair:

Victor R. Lee

Abstract

Research has demonstrated that well into their undergraduate and even graduate education, learners often struggle to understand basic statistical concepts, fail to see their relevance in their personal and professional lives, and often treat them as little more than mere mathematics exercises. This study explored ways help learners in an undergraduate learning context to treat statistical inquiry as mattering in a practical research context, by inviting them to ask questions about and analyze large, real, messy datasets that they have collected about their own personal lives (i.e., self-data). This study examined the conditions under which such an intervention might (and might not) successfully lead to a greater sense of the relevance of statistics to undergraduate learners.

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