Breaking it Down: Engineering Student STEM Confidence at the Intersection of Race/Ethnicity and Gender

Litzler, Elizabeth; Samuelson, Cate; Lorah, Julie

doi:10.1007/s11162-014-9333-z

Cited by 133 publications

(96 citation statements)

References 71 publications

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“…A student who dreads attending class or participating in a club may wonder if it is the peer group, instructor (Lester, Yamanaka, and Struthers 2016), or her own skill set (Litzler, Samuelson, and Lorah 2014). Women may hesitate to ask questions in class (Sobel, Gilmartin, and Sankar 2016) or underestimate their own abilities when they may simply have different learning styles than those engaged in class (Deemer et al 2014; Kulturel-Konak, Lou D'Allegro, and Dickinson 2011).…”

Section: Classroom Experiencesmentioning

confidence: 99%

The Status of Women in STEM in Higher Education: A Review of the Literature 2007–2017

Blackburn

2017

Science & Technology Libraries

251

155

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Increased efforts to diversify science, technology, engineering, and mathematics (STEM) education in the United States have drastically increased the number of studies offering insight into the experiences of women in STEM programs in higher education. This paper presents a thematic review of the literature regarding their status from 2007 to 2017 including journals, trade magazines, theses, and dissertations. It focuses on areas of recruitment, retention, barriers, and faculty issues. Stereotypes, biases, campus culture, classroom experiences, identity, and sense of belonging are also explored. The author additionally identifies gaps and suggests related areas for new research as well as implications for librarians.

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Section: Classroom Experiencesmentioning

confidence: 99%

The Status of Women in STEM in Higher Education: A Review of the Literature 2007–2017

Blackburn

2017

Science & Technology Libraries

251

155

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“…List of Tables Litzler, Samuelson, and Lorah (2014) examined the relationship between various covariates, such as student perception of professors and student confidence. It would be interesting to test whether this relationship differs by group membership.…”

Section: List Of Figuresmentioning

confidence: 99%

“…In other words, an interaction between perception of professors and gender is present. Further, the data for this study (Litzler et al, 2014) included students nested within multiple schools, indicating that a multilevel model would be appropriate, given the non-independence of individual student observations. Moderator hypotheses such as these can be examined with moderated multiple regression models and this can be done within a multilevel framework for data that includes nesting.…”

Section: List Of Figuresmentioning

confidence: 99%

“…Data from this project has been analyzed previously to examine patterns of attrition and covariates to attrition among undergraduate engineering students (Litzler & Young, 2012) and to examine engineering student confidence and how it varies as a function of gender and race/ethnicity as well as various self-reported measures of climate and student perception (Litzler et al, 2014). More details regarding the participating schools and survey methodology can be found in previously published work (see Litzler & Lorah, 2013;Litzler et al, 2014;Litzler & Young, 2012). The survey used for this analysis was fielded in 2012 within 15 engineering schools.…”

Section: Datamentioning

confidence: 99%

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Estimating individual-level interaction effects in multilevel models: a Monte Carlo simulation study with application

Lorah

2017

Journal of Applied Statistics

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Moderated multiple regression (MMR) provides a useful framework for understanding moderator variables. When the relationship between an independent variable (predictor) and a dependent variable (criterion) varies as a function of a third variable, that third variable is considered a moderator of the predictor-criterion relationship. Moderated relationships can also be examined within datasets that include nesting, for example individuals might be nested within groups. However, the literature is not clear on the best way to assess data for significant moderating effects, particularly within a multilevel modeling framework. This study explores potential ways to test moderation at the individual level (level 1) within a 2-level multilevel modeling framework, with varying effect sizes, cluster sizes, and numbers of clusters that represent realistic conditions in applied educational research. The study examines five potential methods for testing interaction effects: the Wald test, F-test, likelihood ratio test, BIC, and AIC.For each method, the simulation study examines how Type I error rates vary as a function of number of clusters and cluster size and how power varies as a function of number of clusters, cluster size, and interaction effect size. Following the simulation study, an applied study uses real data to assess interaction effects using the same five methods. Results indicate that the Wald test, F-test, and likelihood ratio test all perform similarly in terms of Type I error rates and power. Type I error rates for the AIC are more liberal, and for the BIC typically more conservative. A four-step procedure for applied researchers interested in examining interaction effects in multi-level models is provided. gender is present. Further, the data for this study (Litzler et al., 2014) included students nested within multiple schools, indicating that a multilevel model would be appropriate, given the non-independence of individual student observations. Moderator hypotheses such as these can be examined with moderated multiple regression models and this can be done within a multilevel framework for data that includes nesting. The results of these types of models can represent important and relevant contributions to the literature. This study will investigate methods for testing multilevel moderated regression models with interaction effects at the individual level only (or more generally, at level-one only). Within this study, this model includes a continuous dependent variable, a continuous independent variable, and a binary moderator variable. Methods for testing this interaction effect will be evaluated on Type I error rates and power based on a simulation study and an applied study will follow to illustrate the technique. An introduction to moderation, multilevel models, and testing for interaction effects follows in this chapter.

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“…[3][4][5] In STEM fields, underrepresented minorities are particularly vulnerable to disengagement with the "STEM culture" (leaving a STEM field of study) due to beliefs about their ability to succeed in STEM, even when accounting for prior academic preparation. 6 The relationship between institutional or disciplinary culture, race, and ethnicity is especially relevant to racial and ethnic minorities that are even more underrepresented in STEM than they are in most other fields. 7,8 In 2014, 10.5 million foreign-born persons had a college degree or higher, representing about twenty-nine percent of the total 36.7 million U.S. foreign-born population ages 25 and over.…”

mentioning

confidence: 99%

Board # 87 : Native-Born and Foreign-Born Black Students in STEM: Addressing STEM Identity and Belonging Barriers and their Effects on STEM Retention and Persistence at the Two Year College

Leggett-Robinson

Villa²,

Davis

2017 ASEE Annual Conference &Amp; Exposition Proceedings

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Background Two-year colleges provide a rich, diverse student population (people of color, women, older students, veterans, foreign born students, international students, first-generation college-goers, low-income, and working parents) with access to higher education who thus have the potential to increase participation of underrepresented students in STEM. Unfortunately, graduation and transfer rates for black students (native-born and foreign-born) are still significantly lower than those of their non-black counterparts (with the exception of Pacific Islanders and Native Americans) at both the two-year college and four-year college.Factors influencing retention and persistence in STEM majors are diverse and often interconnected. Leading reasons for low STEM retention and persistence at both the two-year and four-year colleges are: uninspiring introductory courses, lack of math preparation, and an academic culture not welcoming of women, minorities, and non-traditional students. 1,2 Numerous efforts have been initiated to increase the numbers and success of underrepresented students majoring in STEM disciplines; however, factors influencing retention and persistence of STEM majors continue to be problematic.It is important to focus on the culture of STEM education because the social, psychological, and structural dimensions of STEM in these institutions influence how students connect their personal identities to their academic domains and view themselves as learners in those domains (their academic identities), which subsequently affects their efforts and achievement. [3][4][5] In STEM fields, underrepresented minorities are particularly vulnerable to disengagement with the "STEM culture" (leaving a STEM field of study) due to beliefs about their ability to succeed in STEM, even when accounting for prior academic preparation. 6 The relationship between institutional or disciplinary culture, race, and ethnicity is especially relevant to racial and ethnic minorities that are even more underrepresented in STEM than they are in most other fields. 7,8 In 2014, 10.5 million foreign-born persons had a college degree or higher, representing about twenty-nine percent of the total 36.7 million U.S. foreign-born population ages 25 and over. Foreign-born Americans are earning STEM degrees in disproportionately large numbers, compared to the native-born U.S. population. 9 Thirty-three percent of all graduates with engineering degrees are foreign-born, twenty-seven percent are graduates in computers, math, and statistics, and twenty-four percent are in physical sciences. 9,10 Of the entire foreign-born population receiving STEM degrees, foreign-born blacks and native-born blacks make up only eight percent of all STEM graduates. 11 Surprisingly, however, foreign-born black students are enrolling in post-secondary institutions and graduating at higher rates than native-born black students. 12 In today's society, ethnicity and nationality are often subsumed by race and thus the distinctions among people of the same race are c...

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Breaking it Down: Engineering Student STEM Confidence at the Intersection of Race/Ethnicity and Gender

Cited by 133 publications

References 71 publications

The Status of Women in STEM in Higher Education: A Review of the Literature 2007–2017

The Status of Women in STEM in Higher Education: A Review of the Literature 2007–2017

Estimating individual-level interaction effects in multilevel models: a Monte Carlo simulation study with application

Board # 87 : Native-Born and Foreign-Born Black Students in STEM: Addressing STEM Identity and Belonging Barriers and their Effects on STEM Retention and Persistence at the Two Year College

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