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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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Posted ContentDOI

Career self-efficacy disparities in underrepresented biomedical scientist trainees

TL;DR: In this paper , the authors examined racial, ethnic, and gender disparities in career self-efficacy among 6077 US citizens and US naturalized graduate and postdoctoral trainees.
Journal ArticleDOI

Apoyo educativo y de pares en las disciplinas en ciencia, tecnología, informática y matemáticas

TL;DR: In this article, a focus group session was held with students of the mathematics career to identify the support received by high school students in the decision-making process for careers in science, technology, engineering and mathematics.
Journal ArticleDOI

The long-term effects of students’ economic competencies on the transition from school to university in the international context

TL;DR: In this paper , the authors systematically embeds findings from a Swiss longitudinal study in the international context and compare it with other countries that also provide substantial research on economic education (e.g., the U.S. and Japan).
Proceedings ArticleDOI

An Experiment-based Approach in the Context of Electrified Aviation to Increase the Interest of K-12 Pupils in STEM

TL;DR: In this paper , an approach to combine inductive and deductive learning methods with hands-on experiences to increase the interest of K-12 pupils in Science, Technology, Engineering and Mathematics (STEM).
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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