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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

Shenandoah Valley Governor’s School: A Profile of a Shared-Day STEM Program in a Rural Area

TL;DR: Shenandoah Valley Governor's School as mentioned in this paper is an Academic-Year Governor's school sponsored by the Virginia Department of Education, which is located in Shenandoah, VA. Juniors and seniors from seven high schools attend this shared day, selective regional school.

Career Regret among University Students from Turkey: A Test of the Social Cognitive Career Theory

TL;DR: In this paper, a study aimed to test the predictors of career regret among university students and found that higher levels of negative affect was associated with career regret because of low career self-efficacy and outcome expectations from one's career.
Journal ArticleDOI

Discussion on the Role of Computer Technology in Promoting Students' Interest in Learning

TL;DR: In this article, the role of computer technology in promoting students' interest in learning is discussed, where the student community is regarded as the teaching main body, becomes the study the master, the student may act according to own study progress condition to carry on the content repetition study.
Journal ArticleDOI

Socioeconomic Differences in North Carolina College Students’ Pathways Into STEM

TL;DR: In this article , the authors identify factors related to LSES students' odds of declaring and graduating with a STEM degree and test whether those factors work in similar ways for students from higher socioeconomic groups.
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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