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Identifying Advantages to Teaching L...

Clement, Kit Harris.

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Identifying Advantages to Teaching Linear Regression in a Modeling and Simulation Introductory Statistics Curriculum.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Identifying Advantages to Teaching Linear Regression in a Modeling and Simulation Introductory Statistics Curriculum./
Author:	Clement, Kit Harris.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:	215 p.
Notes:	Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
Contained By:	Dissertations Abstracts International85-01B.
Subject:	Mathematics education. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30523366
ISBN:	9798379779467

Identifying Advantages to Teaching Linear Regression in a Modeling and Simulation Introductory Statistics Curriculum.
Clement, Kit Harris.

Identifying Advantages to Teaching Linear Regression in a Modeling and Simulation Introductory Statistics Curriculum. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 215 p.

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

Thesis (Ph.D.)--Portland State University, 2023.

This item must not be sold to any third party vendors.

Statistical association is a key facet of statistical literacy: claims based on relationships between variables or ideas rooted in data are found everywhere in media and discourse. A key development in introductory statistics curricula is the use of simulation-based inference, which has shown positive outcomes for students, especially in regards to statistical literacy and conceptual understanding. In this dissertation project, I investigate students from the Change Agents for the Teaching and Learning of STatistics (CATALST) curriculum in activities I designed for learning statistical association and linear regression. First, I analyzed the informal line fitting strategies of CATALST students. Findings suggest that students still face many challenges in informal line fitting, but their use of the offsetting distances criterion may be a future point of focus for teaching and activity development. Next, I compared student outcomes in a traditional course and a CATALST course on their ability to recognize the need for inference and hypothesis testing. Results revealed that CATALST students were more prepared to learn inference in their course and made greater gains by the end of the linear regression unit. Finally, I examine CATALST students' inferential reasoning in light of frameworks that identify challenges in learning simulation-based inference. Based on the success CATALST students demonstrated, I propose technology innovations to the simulation software so that the classroom can better focus on learning statistics rather than technology. Overall, this dissertation provides insights into activities that expand the existing CATALST curriculum to include linear regression and shares the benefits of leveraging this simulation-based curriculum while highlighting challenges these students experienced and directions for future work to address these challenges.

ISBN: 9798379779467Subjects--Topical Terms:

641129
Mathematics education.
Subjects--Index Terms:

Inference

Identifying Advantages to Teaching Linear Regression in a Modeling and Simulation Introductory Statistics Curriculum.
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245 1 0 $a Identifying Advantages to Teaching Linear Regression in a Modeling and Simulation Introductory Statistics Curriculum.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2023
300 $a 215 p.
500 $a Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
500 $a Advisor: Thanheiser, Eva;Noll, Jennifer.
502 $a Thesis (Ph.D.)--Portland State University, 2023.
506 $a This item must not be sold to any third party vendors.
520 $a Statistical association is a key facet of statistical literacy: claims based on relationships between variables or ideas rooted in data are found everywhere in media and discourse. A key development in introductory statistics curricula is the use of simulation-based inference, which has shown positive outcomes for students, especially in regards to statistical literacy and conceptual understanding. In this dissertation project, I investigate students from the Change Agents for the Teaching and Learning of STatistics (CATALST) curriculum in activities I designed for learning statistical association and linear regression. First, I analyzed the informal line fitting strategies of CATALST students. Findings suggest that students still face many challenges in informal line fitting, but their use of the offsetting distances criterion may be a future point of focus for teaching and activity development. Next, I compared student outcomes in a traditional course and a CATALST course on their ability to recognize the need for inference and hypothesis testing. Results revealed that CATALST students were more prepared to learn inference in their course and made greater gains by the end of the linear regression unit. Finally, I examine CATALST students' inferential reasoning in light of frameworks that identify challenges in learning simulation-based inference. Based on the success CATALST students demonstrated, I propose technology innovations to the simulation software so that the classroom can better focus on learning statistics rather than technology. Overall, this dissertation provides insights into activities that expand the existing CATALST curriculum to include linear regression and shares the benefits of leveraging this simulation-based curriculum while highlighting challenges these students experienced and directions for future work to address these challenges.
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653 $a Modeling
653 $a Simulation
653 $a Statistical association
653 $a Statistics education
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710 2 $a Portland State University. $b Mathematics. $3 3279442
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792 $a 2023
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30523366