– The results show that the reform increased university enrollment rates for both genders.
-The reform increased students’ willingness to enroll at university for males and females alike. The reform effect of university enrollment can be assessed as meaningful with 1.3 and 1.2 percentage points for females and males, respectively.
– With regard to choosing STEM as college major, the authors find a
robust positive effect of the high school curriculum reform on males.
– While the results for males indicate that the reform made them more like to choose a STEM major on a statistically significant level, this is not true for females.
– A likely mechanism for the gender difference in major choices is the underlying preferences of men and women.
Current Selections
ClearThe effects of a high school curriculum reform on university enrollment and the choice of college major
Gendered Choices of STEM Subjects for Matriculation Are Not Driven by Prior Differences in Mathematical Achievement
– Gender streaming among STEM fields appears already in secondary school.
– Girls are under-represented in physics, IT and advanced mathematics.
– This pattern is not driven by gender differences in prior achievement in numeracy.
– Socio-economic disadvantage has a greater adverse effect on boys than on girls.
– There is significantly less gender streaming among STEM fields in all-girls schools.
– Students with a language background other than English choose STEM fields with greater frequency than other students, reflecting their comparative advantage, while exhibiting more markedly gendered subject choices, indicating a role for cultural factors.
An Advisor Like Me: Does Gender Matter?
– Gender congruence in the student-adviser relationship is particularly helpful for academically weak students and students without STEM-orientation.
– Gender congruence has no significant impact on students with STEM-orientation regardless of whether their high-school GPAs are below or above the median.
– For students without STEM orientation, gender congruence helps students with below-median high school GPA improve their student outcomes both on the extensive and intensive margins, while helping students with above-median high school GPA improve their outcomes only on the extensive margin.
-The authors find that gender congruence in the student-adviser relationship has a positive and significant effect on the odds of retention and on cumulate GPA upon graduation.
– The authors uncover that much of the gender congruence effect
on the extensive margin tends to be concentrated in the freshman and sophomore years, while the gender congruence effect on the intensive margin is less immediate and shows up only in cumulative GPA upon graduation.
– Student-adviser gender congruence is found to work differently for students with different backgrounds and interests.
– Gender congruence has no significant impact on students with STEM-orientation regardless of whether their high-school GPAs are below or above the median.
How School Socioeconomic Status Affects Achievement Growth across School Transitions in Early Educational Careers
– Findings suggest that a student’s elementary SES composition has a legacy effect on middle school achievement growth net of his
or her own achievement growth and middle school SES composition.
– SES composition effects differ depending on the timing of exposure and a student’s individual free and reduced lunch (FRL) status.
– Findings suggest that early education contexts are critical for math achievement growth in general.
– The authors’ findings show that school segregation by socioeconomic status is problematic for achievement growth for
all students.
– Disadvantages from the elementary school context carry over to the middle school context, and the SES composition effect of students’ middle school depends on students’ prior school experiences.
Inequality in Reading and Math Skills Forms Mainly before Kindergarten: A Replication, and Partial Correction, of ‘‘Are Schools the Great Equalizer?’’
– When the authors use the new test scores, they find that variance is substantial at the start of kindergarten and does not grow but actually shrinks over the next two to three years. This finding, which was not evident in the original Great Equalizer
study, implicates the years before kindergarten as the primary source of inequality in elementary reading and math.
– Total score variance grows during most summers and shrinks during most school years, suggesting that schools reduce inequality overall.
– Changes in inequality are small after kindergarten and do not replicate consistently across grades, subjects, or cohorts. That said, socioeconomic gaps tend to shrink during the school year and grow during the summer, while the black-white gap tends to follow the opposite pattern.
– Socioeconomic gaps tend to shrink during the school year and grow during the summer, while the black-white gap tends to follow the opposite pattern.
– Inequality in basic reading and math skill originates mainly in early childhood, before kindergarten begins.
Foreign Peer Effects and STEM Major Choice
This paper aims to estimate the impact of foreign peers on native STEM major choice.
Female Faculty Role Models, Self-efficacy and Student Achievement
This study estimates the effect of having a female instructor, the effects of measures of self-efficacy, and the interaction effects of measures of self-efficacy and having a female instructor on female and male student grade performance.
Choice of Majors: Are Women Really Different from Men?
– High school academic preparation, faculty gender composition, and major returns have little effect on major switching behaviors, and women and men are equally likely to change their major in response to poor grades in major-related courses.
– Women in male-dominated majors do not exhibit different patterns of switching behaviors relative to their male colleagues.
– Women are more likely to switch out of male-dominated STEM majors in response to poor performance compared to men.
– It takes multiple signals of lack of fit into a major (low grades, gender composition of class, and external stereotyping signals) to impel female students to switch majors.
Gender Differences in the Choice of Major: The Importance of Female Role Models
This paper asks whether exposure to female role models may be an effective way to induce more
women to major in a male-dominated field.
Can learning communities boost success of women and minorities in STEM? Evidence from the Massachusetts Institute of Technology
– Author finds no statistically significant effects on academic outcomes for ESG enrollees generally, but women who participate in the program have higher GPAs and complete more credits of coursework.
– Minority students are more likely to major in math, computer science, or electrical engineering after participating in the ESG program.
– Though quite noisy, the results are suggestive that women and minorities in STEM may benefit from learning communities.
– Author finds evidence that female instructors are particularly beneficial for female students at MIT. However, the magnitude of the estimates suggests that the gender-mix of ESG instructors cannot account for most of the academic effects the author observes for female students.
Decomposing the Racial Gap in STEM Major Attrition: A Course-Level Investigation
This paper examines differences in STEM retention between minority and non-minority
undergraduate students. It examines the role of ability in the switching decision and timing, they estimate STEM and non-STEM ability, and then compare the joint distribution of students who switch out of STEM versus STEM stayers.
Gender Streaming and Prior Achievement in High School Science and Mathematics
– Gendered choices they make remain largely intact after conditioning on prior test scores, indicating that these choices are not driven by differences in perceived mathematical ability, or by boys’ comparative advantage in mathematics.
– Girls who choose matriculation electives in physics and computer science score higher than boys, on average.
– Girls and boys react differently to early signals of mathematical and verbal ability.
– Girls are less adversely affected by socioeconomic disadvantage.
– Girls score higher in all four subjects, with a greater advantage in
language arts than in mathematics and science, implying that boys have a comparative advantage in mathematics and science.
– There is a strong pattern of gender streaming in the choice of electives in science and mathematics. The share of boys choosing advanced physics or computer science is more than twice that of girls; the share of boys choosing advanced mathematics is about 20% higher; while the share of girls choosing advanced biology is about 60% higher than boys and their share in advanced chemistry is 40% higher.
– For physics or computer science and for advanced mathematics, accounting for the observed gender difference in the distribution of prior mathematics achievement widens the gender gap very slightly.
– For biology and chemistry, accounting for differences in prior
achievement reduces the gap favoring girls by 0.6 percentage points.
– In the regression, as girls do slightly better than boys in eighth-
grade mathematics, controlling for prior achievement in mathematics increases the gender gap favoring boys in physics or computer science and in advanced mathematics, by 1.0 and 1.2 percentage points respectively while reducing the gender gap favoring girls in biology or chemistry by 0.8 of a percentage point.
– The largest effect is in advanced mathematics and the smallest in biology or chemistry, in line with the relevance of mathematical ability for each subject.
– All prior scores exhibit a statistically significant, positive (and in most cases convex) relationship with the probability of choosing a science or mathematics elective.
– An interaction term, the product of the mathematics and Hebrew scores, also has a significant positive effect.
– Boys’ and girls’ different propensities to choose science and mathematics electives are partly a reflection of their different responses to prior signals of ability. A signal of strong mathematical ability has a positive effect on both boys and girls for all three categories, but the effect is stronger for boys with regard to choosing advanced mathematics and physics or computer science, and stronger for girls with respect to choosing biology or chemistry; and a similar pattern applies to prior achievement in science.
– Selection of science and mathematics electives increases in parents’ education. The rate of increase is more moderate in biology or chemistry; and the share of girls declines with parents’ education in all electives. These findings are a further indication that boys benefit from a strong family background more than girls.
– The size of the gender gap increases in parental education for all electives, and more steeply in the male-dominated subjects, mathematics and physics or computer science, showing again that boys benefit more from a strong family background.
– Of the three groups, coeducational religious schools serve a population of students from markedly lower income groups, and achieve the lowest GEMS scores in all subjects for both male and female students in these schools. Coeducational non-religious schools and single-sex religious schools have more similar student populations.
– In non-religious schools, girls outperform boys, whereas boys outperform girls in religious schools.
– Single-sex religious schools have the highest matriculation rates, followed by coeducational non-religious schools.
The Impact of Inclusive STEM High Schools on Student Achievement
To estimate the impact of “inclusive” science, technology, engineering, and mathematics (STEM) high schools.
Characteristics of US Students That Pursued a STEM Major and Factors That Predicted Their Persistence in Degree Completion
1) What are the characteristics of students’ who declared a STEM major? 2)What are the characteristics of students who completed a STEM major? 3)What factors influence students who persisted to complete a STEM major?
In the Guise of STEM Education Reform: Opportunity Structures and Outcomes in Inclusive STEM-Focused High Schools
1) How do eight inclusive (nonselective) urban public (non-charter) high schools (two STEM-focused and two comprehensive, traditionally structured) approach and organize opportunities for STEM for low-income historically underrepresented minorities? 2) What written and enacted opportunity structures are available, over a three-year time span (2010-2013), for high-achieving (top track) students at the four STEM-focused schools? 3) How do select teachers and counselors perceive available opportunity structures? 4) How do these opportunity structures position high-achieving students for further study and a career in STEM?
Using Multiple Measures to Make Math Placement Decisions: Implications for Access and Success in Community Colleges
Whether boosted students are equally likely to succeed when compared with other students in the higher-level course despite having lower raw placement test scores.
Characteristics of Schools Successful in STEM: Evidence from Two States' Longitudinal Data
This report estimates school effectiveness in science and mathematics to identify and describe both successful and un-successful schools in STEM fields.
How Well Does the SAT and GPA Predict the Retention of Science, Technology, Engineering, Mathematics, and Business Students
This study examined if a higher college preparatory GPA and a higher aggregate score on the SAT helped predict the retention of science, technology, engineering, mathematics, and business students.
Low-Income Engineering Students: Considering Financial Aid and Differential Tuition
1) What are the rates of participation in Engineering undergraduate programs at two public, research universities by socio-economic status? 2) What is the actual cost of pursuing a degree in Engineering at two public, research universities by socio-economic status? 3) How does financial aid (e.g., Pell Grants, state aid, institutional aid) fluctuate over time for low-income and other students in Engineering and non-Engineering fields? 4) What are the graduation rates for students in Engineering and non-Engineering majors, by socio-economic status?
Who succeeds in STEM studies? An analysis of Binghamton University undergraduate students
Who is more likely to enter and graduate with a STEM major?
The Role of Peers and Grades in Determining Major Persistence in the Sciences
This paper examines the determinants of entering and then persisting in physical and life science majors. Also, it investigates the impact of one’s peers on major persistence.
The effect of instructor race and gender on student persistence in STEM fields
To see if the race or gender of the instructor effects persistence of initial STEM majors in a STEM field after the first semester and first year.
Attrition in STEM Fields at a Liberal Arts College: The Importance of Grades and Pre-Collegiate Preferences
To quantify the important factors responsible for the high attrition rates in STEM majors, particularly in relation to gender.
Academic Success for STEM and Non-STEM Majors
1) What background characteristics, ability measures, financial support systems, and academic support mechanisms help explain retention and/or graduation for students in both STEM and non-STEM majors by the end of the sixth year? 2) Are the predictors of retention and/or graduation by the end of the sixth year different for STEM and non-STEM majors? 3) Are underrepresented students in STEM majors more likely than traditional students in STEM majors to be retained/graduated in six years when controlling for selected background, environmental, financial, and academic measures?