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A Mathematical Modelling Approach to Analyze the Dynamics of Math Anxiety.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A Mathematical Modelling Approach to Analyze the Dynamics of Math Anxiety./
作者:	Soysal, Dilek.
面頁冊數:	1 online resource (180 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-02, Section: B.
Contained By:	Dissertations Abstracts International84-02B.
標題:	Mathematics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29324924click for full text (PQDT)
ISBN:	9798841781479

A Mathematical Modelling Approach to Analyze the Dynamics of Math Anxiety.
Soysal, Dilek.

A Mathematical Modelling Approach to Analyze the Dynamics of Math Anxiety. - 1 online resource (180 pages)

Source: Dissertations Abstracts International, Volume: 84-02, Section: B.

Thesis (Ph.D.)--University of Missouri - Kansas City, 2022.

Includes bibliographical references

The main objective of this study is to develop a mathematical modeling framework for a deeper understanding of dynamics of math anxiety as a contagious process. Borrowing from theories of the spread of infectious disease, we develop two classes of mathematical models representing the spread of math anxiety in math gateway classes. The first mathematical model does not entirely fit with our collected data of math anxiety (n=53, Calculus II & III summer of 2020). However, the second mathematical model, which is a generalization of the first model, can exhibit periodic solutions as observed in the collected data. In addition to the mathematical modeling framework, we have applied a variety of statistical methods and models to analyze the survey data. This includes descriptive analysis of the data, correlation and hypothesis testing, and a machine learning approach, which utilizes the classification and regression tree models to identify key factors associated with math anxiety. These regression tree models include factors such as gender, academic level, number of hours studied, motivation, and confidence. In conclusion, the present work lays the foundation for applying mathematical models to measure the spread of math anxiety in gateway STEM courses.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798841781479Subjects--Topical Terms:

515831
Mathematics.
Subjects--Index Terms:

ConfidenceIndex Terms--Genre/Form:

542853
Electronic books.

A Mathematical Modelling Approach to Analyze the Dynamics of Math Anxiety.
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502 $a Thesis (Ph.D.)--University of Missouri - Kansas City, 2022.
504 $a Includes bibliographical references
520 $a The main objective of this study is to develop a mathematical modeling framework for a deeper understanding of dynamics of math anxiety as a contagious process. Borrowing from theories of the spread of infectious disease, we develop two classes of mathematical models representing the spread of math anxiety in math gateway classes. The first mathematical model does not entirely fit with our collected data of math anxiety (n=53, Calculus II & III summer of 2020). However, the second mathematical model, which is a generalization of the first model, can exhibit periodic solutions as observed in the collected data. In addition to the mathematical modeling framework, we have applied a variety of statistical methods and models to analyze the survey data. This includes descriptive analysis of the data, correlation and hypothesis testing, and a machine learning approach, which utilizes the classification and regression tree models to identify key factors associated with math anxiety. These regression tree models include factors such as gender, academic level, number of hours studied, motivation, and confidence. In conclusion, the present work lays the foundation for applying mathematical models to measure the spread of math anxiety in gateway STEM courses.
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