The Role of Personality in Relation to Gender Differences in School Subject Choices in Pre-University Education

Korpershoek, Hanke; Kuyper, Hans; Werf, Greetje van der

doi:10.1007/s11199-012-0222-7

Cited by 10 publications

(9 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results in model (g) suggest individuals who are less agreeable (i.e., more critical) have a higher probability of persisting in STEM. Korpershoek, Kuyper, and van der Werf (2012) find similar results in examining school subject choices for high school students in the Netherlands.…”

Section: Undergraduate Stem Retention In the United Statessupporting

confidence: 68%

“…Griffith (2010) studied students who were in their first year of college in 1999 and found only 37% of women versus 43% of men persist to graduate with a STEM major. Several studies (e.g., Riegle-Crumb et al, 2012; Xie and Shauman, 2003; Seymour and Hewitt, 1997) have examined the underlying reasons for the differentials in STEM persistence, by examining persistence after controlling for (latent) variables, such as academic achievement (e.g., Maltese and Tai, 2011), math and science identity (Chang, et al, 2011), interest (Sullins, Hernandez and Fuller, 1995), future time perspective (Husman, et al, 2007), sense of community (Espinosa, 2011), goals (Leslie, McClure and Oaxaca, 1998) or personality traits (Korpershoek, Kuyper and van der Werf, 2012). …”

Section: Undergraduate Stem Retention In the United Statesmentioning

confidence: 99%

“…While racial differences in STEM retention are often explained by the comparative disadvantage in academic background that under-represented minorities (URMs) have relative to their white peers, several recent studies (Weinberger, 2012; Riegle-Crumb et al, 2012) question the explanation that gender gaps in STEM retention are due to gaps in math achievement. Others (e.g., Korpershoek, Kuyper and van der Werf, 2012) suggest STEM retention gender gaps may be better explained by personality trait differences.…”

Section: Undergraduate Stem Retention In the United Statesmentioning

confidence: 99%

“…The sub-scale scores are an average of the two items that pertain to each of the Five Factors. Research (e.g., Felder, Felder, and Dietz, 2002; Major, Holland and Oborn, 2012; Korpeshoek et al, 2012; Van Langen, 2005) notes personality traits such as the Big Five may have an effect on gender differences in STEM retention. For the purposes of showing the measurement error bias, the TIPI (in which J = 2 for each of the five latent personality traits) serves as a good example.…”

Section: Undergraduate Stem Retention In the United Statesmentioning

confidence: 99%

“…Despite ongoing work by many colleges and universities, women and under-represented minorities (URMs) are still far less likely to major in the STEM disciplines (NCES, 2009). Using generalized linear models (e.g., linear probability models, logistic regressions, or probit analyses), researchers model the racial and gender STEM retention gaps after controlling for a set of covariates, which often include some latent variable(s) such as e.g., academic achievement (Maltese and Tai, 2011), or personality traits (Korpershoek, Kuyper, and van der Werf, 2012). …”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Correcting for measurement error in latent variables used as predictors

Schofield¹

2015

Ann. Appl. Stat.

View full text Add to dashboard Cite

This paper represents a methodological-substantive synergy. A new model, the Mixed Effects Structural Equations (MESE) model which combines structural equations modeling and item response theory is introduced to attend to measurement error bias when using several latent variables as predictors in generalized linear models. The paper investigates racial and gender disparities in STEM retention in higher education. Using the MESE model with 1997 National Longitudinal Survey of Youth data, I find prior mathematics proficiency and personality have been previously underestimated in the STEM retention literature. Pre-college mathematics proficiency and personality explain large portions of the racial and gender gaps. The findings have implications for those who design interventions aimed at increasing the rates of STEM persistence among women and under-represented minorities.

show abstract

Section: Undergraduate Stem Retention In the United Statessupporting

confidence: 68%

Section: Undergraduate Stem Retention In the United Statesmentioning

confidence: 99%

Section: Undergraduate Stem Retention In the United Statesmentioning

confidence: 99%

Section: Undergraduate Stem Retention In the United Statesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Correcting for measurement error in latent variables used as predictors

Schofield¹

2015

Ann. Appl. Stat.

View full text Add to dashboard Cite

show abstract

Female Robots as Role-Models? - The Influence of Robot Gender and Learning Materials on Learning Success

Pfeifer

Lugrin

2018

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Gender impact on STEM online learning- a correlational study of gender, personality traits and learning styles in relation to different online teaching modalities

Idrizi

Filiposka

Trajkovikj

2023

Multimed Tools Appl

View full text Add to dashboard Cite

STEM (science, technology, engineering and mathematics) education benefits both individuals and society. It supports individuals by increasing their critical-thinking skills, encouraging creativity, as well as providing a basis for new inventions. The underrepresentation of women in STEM is a complex issue with various causes and different approaches of addressing it, where most likely gender differences are caused by desires and choice rather than abilities and performance. This paper explores differences in online and traditional STEM learning based on gender. It examines in detail recently identified patterns of women’s success, their access to STEM online courses, and their overall course experience during such courses. We analyzed results from a case study in which students were enrolled for one semester in two STEM online courses and completed questionnaires about their character traits and learning styles and how they relate to academic performance. The objective of our research is to analyze academic success during traditional classes and online classes, with focus on gender and identify how character traits and learning styles correlate with gender in online classes. The main outcome of our research is that female students, which study in the field of STEM in particular computer science, are trustworthy and autonomous students who can outperform their male counterparts during traditional courses, where during online courses male students still exceed slightly female students. The trait of Consciousness is a success predictor regardless of gender and learning environment, while the trait of Neuroticism has negative impact the traditional learning environment, Extraversion shows negative impact in online learning. Learning styles show gender differences, where female students prefer the style of read/write while male students favor kinesthetic.

show abstract

The Role of Personality in Relation to Gender Differences in School Subject Choices in Pre-University Education

Cited by 10 publications

References 49 publications

Correcting for measurement error in latent variables used as predictors

Correcting for measurement error in latent variables used as predictors

Female Robots as Role-Models? - The Influence of Robot Gender and Learning Materials on Learning Success

Gender impact on STEM online learning- a correlational study of gender, personality traits and learning styles in relation to different online teaching modalities

Contact Info

Product

Resources

About