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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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Journal ArticleDOI

My science class and expected career choices—a structural equation model of determinants involving Abu Dhabi high school students

TL;DR: In this paper, a structural equation model was developed to capture the links between the various constructs of interest in science, out-of-school experiences, attitude toward science, opinion about science class, and opinion about environmental challenges.
Journal ArticleDOI

Engineering Resistors: Engineering Latina/o Students and Emerging Resistant Capital:

TL;DR: The authors examined how Latina/o engineering students, members of a student organization, used their emergent resistant capital in their academic trajectories, and found that they used it to improve their academic performance.
Journal ArticleDOI

Does Career and Technical Education Strengthen the STEM Pipeline? Comparing Students With and Without Disabilities

TL;DR: In this article, the authors evaluated whether two CTE experiences (applied STEM course taking and school-based experiential programs) in high school differentially predict the declaration of STEM college majors for students with and without disabilities.
Journal ArticleDOI

Pathways to the Geosciences Summer High School Program: A Ten-Year Evaluation.

TL;DR: The authors presented results from 10 years of data from collected during a 2-week summer program for high school students in geosciences targeted at participants of Hispanic American origin in El Paso, Texas.
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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