Journal ArticleDOI
Why Students Choose STEM Majors Motivation, High School Learning, and Postsecondary Context of Support
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 ...read more
Citations
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Proceedings ArticleDOI
When Everyone Knows CS is the Best Major: Decisions about CS in an Indian context
Michael Hewner,Shitanshu Mishra +1 more
TL;DR: This paper explores the experience of CS students who due to India's unusual educational system, joined CS with very little knowledge about CS outside of its reputation and suggests that although students generally enjoyed the CS content of their courses, they had a great deal of concern about the lack of freedom in professional programming.
The Impact of Attitudes toward Science and Core Self-Evaluation on Science Achievement and Career Outcomes: A Trajectory-Based Approach
TL;DR: McDermott et al. as mentioned in this paper used growth mixture modeling to uncover unobserved developmental subgroups of students' attitudes toward science and positive core self-concept through their middle and high school years.
Book ChapterDOI
Creative Writing across the Curriculum
TL;DR: In this paper , the authors define and unpack creative writing across the curriculum (CWAC), an increasingly discussed topic in WAC scholarship, in order to argue that CWAC may guide a productive research agenda for STEM/humanities integration.
Journal ArticleDOI
Parent involvement, expectancy values, and STEM outcomes among underrepresented adolescents
TL;DR: In this article, the authors used data from the High School Longitudinal Study: 2009 (HLS: 2009) to examine links among parent involvement and underrepresented students' STEM self-efficacy, utility, interest and achievement.
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.