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Journal ArticleDOI

Why Students Choose STEM Majors Motivation, High School Learning, and Postsecondary Context of Support

Xueli Wang
- 01 Oct 2013 - 
- Vol. 50, Iss: 5, pp 1081-1121
TLDR
In this article, a conceptual framework for understanding the entrance into science, technology, engineering, and mathematics (STEM) majors by recent high school graduates attending 4-year institutions was proposed.
Abstract
This study draws upon social cognitive career theory and higher education literature to test a conceptual framework for understanding the entrance into science, technology, engineering, and mathematics (STEM) majors by recent high school graduates attending 4-year institutions. Results suggest that choosing a STEM major is directly influenced by intent to major in STEM, high school math achievement, and initial postsecondary experiences, such as academic interaction and financial aid receipt. Exerting the largest impact on STEM entrance, intent to major in STEM is directly affected by 12th-grade math achievement, exposure to math and science courses, and math self-efficacy beliefs—all three subject to the influence of early achievement in and attitudes toward math. Multiple-group structural equation modeling analyses indicated heterogeneous effects of math achievement and exposure to math and science across racial groups, with their positive impact on STEM intent accruing most to White students and least ...

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Citations
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DissertationDOI

The Influence of Tape Diagrams and Bar Models on Middle School Students' Proportional Reasoning

TL;DR: This chapter discusses the literature review of proportional reasoning in terms of theoretical framework, conceptual Frameworks, and modes of representation.
Journal ArticleDOI

Engagement in learning mathematics: the role of need for cognition and achievement goals

TL;DR: In this article , the authors examined the relationships between the students' need for cognition, achievement goals and different aspects of engagement in mathematics within the hierarchical model of achievement goals, and found that achievement goals mediated the relationship between the need for knowledge and engagement.
Journal ArticleDOI

Campus Visits: Impact of a College Outreach Strategy on Student STEM Aspirations.

TL;DR: In this paper, a retrospective cohort study of 27 colleges and universities considers data from 1.1 million campus visits and finds that the impact of campus visits on student health and well-being was examined.
Journal ArticleDOI

Perceived abilities or academic interests? Longitudinal high school science and mathematics effects on postsecondary STEM outcomes by gender and race

TL;DR: This paper examined the relationship between high school students' postsecondary STEM major choices and their prior interest and perceived ability in mathematics and found that while both mathematics and science perceived ability positively influence STEM major selection, academic interest in these subjects is a weaker predictor.
References
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Book

Principles and Practice of Structural Equation Modeling

TL;DR: The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
Book

Structural Equation Modeling With Mplus: Basic Concepts, Applications, And Programming

TL;DR: Structural Equation Models: The Basics using the EQS Program and testing for Construct Validity: The Multitrait-Multimethod Model and Change Over Time: The Latent Growth Curve Model.
Book

Structural equation modeling with AMOS: basic concepts, applications, and programming

TL;DR: In this article, the EQS program is used to test the factorial verifiability of a theoretical construct and its invariance to a Causal Structure using the First-Order CFA model.
Book

Social Foundations of Thought and Action: A Social Cognitive Theory

TL;DR: In this paper, models of Human Nature and Casualty are used to model human nature and human health, and a set of self-regulatory mechanisms are proposed. But they do not consider the role of cognitive regulators.
Journal ArticleDOI

Power analysis and determination of sample size for covariance structure modeling.

TL;DR: In this article, a framework for hypothesis testing and power analysis in the assessment of fit of covariance structure models is presented, where the value of confidence intervals for fit indices is emphasized.
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