– School-based hiring is associated with a larger gap in the distribution of teacher quality between advantaged and disadvantaged schools.
– There is an association between school-based hiring and inequality of achievement based on socioeconomic status of students.
– School-based hiring may contribute to exacerbating inequality in learning opportunities and increasing family background’s positive eﬀect on achievement.
– ESCS (a proxy of family SES) is positively associated with student performance in mathematics and science.
– School-based hiring is not associated with student performance on average, but school-based hiring is associated with the larger achievement gap between high- and low-SES students.
– More school autonomy in hiring was associated with a larger gap in the distribution of teacher quality across schools as well as larger socioeconomic achievement inequality.
– School-level mean SES has a positive and significant relationship with math and science achievement.
– School-based hiring is associated with a larger gap in the distribution of teacher quality between advantaged and disadvantaged schools.
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
– 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.
– While controlling for prior achievement and race, gendered differential treatment was negatively associated with math beliefs and achievement, whereas relevant math instruction was positively associated with these outcomes.
– Gendered differential treatment by teachers in the 8th grade negatively related to student math importance and math grade within the same year.
– Gendered differential treatment by teachers in the 11th-grade was negatively related to 11th-grade SCMA.
– In 8th and 11th grade, relevant math instruction was positively related to students’ math importance and SCMA
– 8th-grade and 11th grade relevant math instruction had an indirect effect upon math importance via self-concept of math ability.
– Self-concept of math ability in the 8th grade partially mediated the relationship between 8th-grade relevant instruction and self-
concept of math ability in the 11th-grade.
– Maryland Math Achievement scores in the 9th grade partially mediated the relationship between 8th-grade gendered differential treatment and self-concept of math ability in the 11th grade.
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.
Gender Gaps in Math Performance, Perceived Mathematical Ability and College STEM Education: The Role of Parental Occupation
– All three factors, math achievement, perceived math ability, and parental occupation in a science field, are found to be significant predictors of the probability of majoring in science in college.
– Having a parent working in a science related field is associated with a better performance in math but not necessarily higher levels of perceived math ability, given math performance.
– Most of the observed positive effects of having a parent in a science related occupation seem to be concentrated among females.
– Estimated effects of higher levels of math achievement are about double for boys than for girls. Estimates of perceived math ability are also slightly larger for boys.
– Schools, as opposed to families, may be the primary vehicle for developing effective strategy use practices for students and thus,
targeted interventions may be particularly useful for male students
attending low SES schools.
– One learning strategy (i.e., control strategies) was found to relate signiﬁcantly and positively to achievement.
– These strategies were used more by females and students attending higher SES schools.
– Males and students attending lower SES schools tended to use a greater number of learning strategies that did not relate to achievement, including memorization and elaboration.
– Strategies that did not relate to achievement were used more
frequently by students from higher SES families.
Academic Performance of African American High School Students Related to Socioeconomic Status and School Size
– There was a negative correlation between school level SES and reading at -.50, -.44 for mathematics, and -.35 for science performance.
– There was a positive correlation between school size and reading at .10, .01 for mathematics, and .07 for science performance.
– School level SES and school size had significant impact on school
performance in reading.
– School level SES had significant impact on school performance in mathematics.
– School level SES and school size had significant impact on school performance in science.
Cracking the Code: Girls' and Women's Education in Science, Technology, Engineering and Mathematics (STEM)
The report is intended to stimulate debate and inform STEM policies and programmes at global, regional and national levels. Specifically, it aims to: i) document the status of girls’ and women’s participation, learning achievement, and progression in STEM education; ii) ‘crack the code’, i.e., decipher the factors that contribute to girls’ and women’s participation, achievement and progression in STEM education; and, iii) identify interventions that promote girls’ and women’s interest in and engagement with STEM studies.
– 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 Role of Mothers’ Communication in Promoting Motivation for Math and Science Course-Taking in High School
– There was a signiﬁcant effect of the experimental intervention on course-taking, such that adolescents whose parents received the intervention took more MS in 12th grade, compared with controls.
– There was an indirect effect of personal connections on STEM course-taking through adolescent’s interest.- More years of mother’s education were associated with higher perceptions of adolescents’ math ability.
– Neither mothers’ years of education nor mothers’ perception of adolescents’ math ability predicted number of conversations between mothers and adolescents or personal connections articulated in the interviews.
– Mothers with more years of education generated more elaborated responses in their interview.
– There was a signiﬁcant interaction between number of conversations and elaboration, such that the highest level of interest occurred with high elaboration and few conversations.
– Adolescents whose parents received the intervention reported more UV in 10th grade than those whose parents were in the control group.
– Higher levels of interest in 10th grade predicted more STEM courses taken in 12th grade.
– There was a signiﬁcant interaction between elaboration and number of conversations such that the highest levels of course-taking were achieved either with the combination of high elaboration and fewer conversations, or less elaboration but more conversations.
1) To what extent do students attending inclusive STEM high schools experience more advanced STEM courses, engaging STEM teaching, real-world STEM experiences, and supports for succeeding in STEM courses and applying to college than do students attending other high schools? 2) To what extent do ISHS students’ STEM interests, activities, achievement, and expectations differ from those of demographically similar students attending high schools without a STEM focus? 3) How are the features promoted for inclusive STEM high schools related to student STEM outcomes?
Narrowing Pathways? Exploring the Spatial Dynamics of Postsecondary STEM Preparation in Philadelphia, Pennsylvania
What geographical factors are associated with the postsecondary STEM preparation of students from underrepresented groups in the School District of Philadelphia from middle to high school?
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.
Does it Matter Who Your Schoolmates Are? An Investigation of the Association between School Composition, School Processes and Mathematics Achievement in the Early Years of Primary Education
(1) What are the effects of school composition with regard to prior math achievement, SES, ethnicity and sex on mathematics achievement at the end of the second grade? (2) Are there differential school composition effects? In other words: are all students affected equally by their school composition or are some specific subgroups more sensitive to their school composition than others? (3) Do certain school processes mediate the association between school composition and mathematics achievement at the end of the second grade?
Do teachers’ instructional practices differentially affect the mathematics achievement of kindergarten students whose backgrounds differ in terms of their race/ethnicity, socioeconomic status (SES), and mathematic academic readiness?
Is housing status a predictor of student achievement in a large urban district, even after controlling for common correlates like income and race? Is the homelessness effect mediated by attendance? What school-level factors predict homeless student achievement?
H1:As black/white school dissimilarity increase, the black/white achievement gap increases H2:As exposure of black students to white students increases, the black/white achievement gap decreases H3: As exposure of black students to other minority students increases, the black/white achievement gap increases or remains stable H4: As black students become increasingly isolated by themselves, the black/white achievement gap increases.
Academic Achievement Trajectories of Adolescents from Mexican and East Asian Immigrant Families in the United States
What are the growth patterns of academic achievement of adolescent students from immigrant families?
The Effects of Single-Sex Compared With Coeducational Schooling on Mathematics and Science Achievement: Data From Korea
– Results for eighth graders indicated no differences between students in single-sex and coeducational schools in mathematics and science achievement.
– Results from the 2003 TIMSS data replicated the finding: students’ mathematics and science achievement was unrelated to the gender composition of their school.
– For both the 2007 and the 2003 data sets, students’ performance was consistently significantly predicted by factors related to socioeconomic status; students (both boys and girls) performed better on the mathematics and science exams when their fathers had more education, their families had more resources, and a lower proportion of their schoolmates came from economically disadvantaged families.
– Both boys’ and girls’ mathematics performance was predicted by the amount of time spent on homework; students do worse when they spend relatively more time on mathematics homework (or students spend more time on homework when they are performing poorly).
1) What is the extent of racial, socioeconomic, and linguistic segregation among U.S. high schools? 2) To what degree are student’s cognitive and non-cognitive skills due to school effects and to individual differences among students? 3) What are the relative magnitudes of the effects of socioeconomic, racial, and linguistic segregation on cognitive and non-cognitive skills compared with the effects of student socioeconomic status, ethnic background, and English language status? 4) To what degree does each of three school mechanisms (school inputs, peer influences, and school practices) mediate the effects of school segregation?
How much variation is there in topic coverage and use of instructional tasks among advanced mathematical courses with the same title? To what extent is there classroom level variation and conditioning on classroom level minority composition for courses of the same title?
Student and high-school characteristics related to completing a science, technology, engineering or mathematics (STEM) major in college
What is the relationship between completing a particular high-school mathematics curriculum and completing a STEM major in college? What is the relationship between student and high-school characteristics and performance in college level mathematics? Can the relationship be generalized across high schools of varying sizes, percentages of college-bound students, SES, and location in the US?
The More Things Change, the More They Stay the Same? Prior Achievement Fails to Explain Gender Inequality in Entry Into STEM College Majors Over Time
This study aims to provide a critical and thorough examination of the extent to which prior achievement can explain inequitable levels of gender representation in STEM fields of study.
Would reallocating immigrant students improve total student achievement and/or benefit the educational outcome of immigrant students?
Ethnic Matching, School Placement, and Mathematics Achievement of African American Students from Kindergarten Through Fifth Grade
1) Do African American students perform better on mathematics achievement test when taught by an African American teacher? 2) What is the effect of African American teachers on the mathematics outcomes of African American students by gender, school poverty, percentage of minorities in school, and type of community?
Examines the differential effects of teachers on female, minority, and low-socioeconomic status (SES) students’ achievement in Grade 4.
Extends previous research regarding gender differences in the effect of peer SES on reading and math scores among 4th grade Chicago Public School students
Who Wants to Have a Career in Science or Math? Exploring Adolescents' Future Aspirations by Gender and Race/Ethnicity
The authors investigate how different racial/ethnic and gender subgroups compare to White males in terms of adolescent career aspirations in science and math, further considering the role that achievement and attitudes may play in shaping disparities at this early point in occupational trajectories.
Family and Contextual Socioeconomic Effects Across Seasons: When Do they Matter for the Achievement Growth of Young Children?
School & neighborhood contexts influence on differences in children’s achievement growth during the kindergarten and first-grade years across seasons.
Analyze associations between the black-white and Latino-white test score gaps and changes in school minority composition.
Teacher Credentials and Student Achievement in High School. A Cross-Subject Analysis with Student Fixed Effects
Examining the relationship between teacher credentials and student achievement in high schools, especially in the core courses taken early in a student’s high school career.
Equity in Mathematics and Science Outcomes: Characteristics Associated with High and Low Achievement on PISA 2006 in Ireland
Examines student and school background characteristics associated with low and high achievement in mathematics and science on the Programme for International Student Assessment.
Perceived School and Neighborhood Safety, Neighborhood Violence and Academic Achievement in Urban School Children
This study utilizes data obtained from the NIfETy Method, child self-report data related to students’ sense of safety, and standardized test scores to better understand the relationship betweenperceived community and school safety, neighborhood violence and school performance in 3rd-5th graders in a mid-Atlantic urban school system.
The authors investigate whether racially diverse high schools offer equality of educational opportunity to students from different racial and ethnic groups. This is examined by measuring the relative representation of minority students in advanced math classes at the beginning of high school and estimating whether and how this opportunity structure limits the level of achievement attained by African American and Latino students by the end of high school.
Explored various kinds of individual and school compositional factors that might produce differences in students’ growth in math and eohs math.
Does the SES of the School Matter? An Examination of Socioeconomic Status and Student Achievement Using PISA 2003
The relationship between school SES and student outcomes.
International Evidence on Ability Grouping with Curriculum Differentiation and the Achievement Gap in Secondary Schools
Review what research from other developed countries says regarding: ability grouping and achievement, achievement gap, etc.
Housing Policy is School Policy: Economically Integrative Housing Promotes Academic Success in Montgomery Count, Maryland
Examination of elementary school math and reading performances of public housing students from very-low-poverty to moderate-poverty level neighborhoods to determine effects of economic integration on performance.
Examine long-term influences of high school racial composition on students’ later racial isolation in the workplace in 1994 & 2000.