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Activity Number: 284 - Assessment Tools in Statistics and Data Science Education
Type: Contributed
Date/Time: Tuesday, August 9, 2022 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and Data Science Education
Abstract #323477
Title: The Role of Context in Developing Statistics Assessment Items
Author(s): Laura Ziegler* and Jennifer Kaplan and Angela Broaddus
Companies: Iowa State University and Middle Tennessee State University and Benedictine College
Keywords: Statistics Education; Introductory Statistics; Assessment; Learning Map Model

In this presentation we will describe the development of assessment items created as part of the NSF funded StatLM Project. The Statistics Learning Map (StatLM) is a graphical representation of learning outcomes related to a single quantitative variable for an undergraduate introduction to statistics course. The StatLM includes a proposed hierarchy of how learning outcomes are related to each other. In order to provide evidence of validity of the proposed hierarchy, assessment items were developed for a subset of learning outcomes in the StatLM. For each learning outcome, four items were written where the statistical question was the same, but the context was different. The items were reviewed by statistics education experts, a language specialist, and multiple reviewers who focused on diversity, equity, and inclusion. The items were piloted at multiple stages of development. The presentation will describe challenges associated with item development with a focus on the relationship between item context and student responses.

Authors who are presenting talks have a * after their name.

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