Disparities in Access to Well-Qualified, Well-Supported Special Educators Across Higher- Versus Lower-Poverty Schools Over Time

Scholars have documented long-standing disparities in access to well-qualified, well-supported teachers, including disparities in access to special education teachers (SETs), based on student socioeconomic status. In response, policy initiatives have aimed to incentivize teaching in higher-poverty schools. Thus, we examined changes over time in disparities between SETs’ demands and resources (including internal resources, such as qualifications, and school-based resources, such as adequate materials), using multiple waves of the nationally representative Schools and Staffing Survey. We found that, by one metric, disparities in certification have closed since 2000. However, SETs in higher poverty schools are significantly more likely to work in self-contained settings than those in lower-poverty schools, and disparities in school-based resources continue to be significant, such that SETs in higher-poverty schools were significantly more likely to teach in self-contained classes, rated teacher cooperation significantly lower, and reported having significantly weaker access to material resources.

Relationships Among Band Festival Ratings, Director Gender, and Other Selected Factors

The purpose of this study was to examine relationships among high school band festival ratings and director gender as well as school locale, school size, student socioeconomic status (SES), student race, repertoire difficulty, and ensemble name. Data included overall ratings of bands ( N = 257) that performed at District Concert Assessments held across the state of Virginia during 2019 as well as demographic information from the National Center for Education Statistics. Statistical analysis of a subset of these performances ( n = 151) revealed a statistically significant association between ratings and director gender, with male-directed ensembles more likely to receive a “I” rating than female-directed ensembles. However, hierarchical logistic regression revealed that repertoire difficulty and ensemble name were the best predictors of whether an ensemble would receive a “I” rating. Implications include the need to examine why female band directors may choose less difficult repertoire than male directors and to explore strategies for making the secondary band teaching profession more equitable and inclusive.

Teacher Salary Differentials and Student Performance: Are They Connected?

We examine the relationship between district level student achievement and teacher average salary in Ohio from academic year 2013-14 to academic year 2018-19. Utilizing panel data, the following district level characteristics were controlled for: average teacher experience, average teacher degree-level, student socioeconomic status, race, student attendance rate, pupil support expenditure per equivalent pupil and administration expenditure per equivalent pupil. Using a random effects regression our findings suggest that higher pay can impact student growth. When we partition our sample quintiles by poverty level, we find that teacher salary is only significant for the top quintiles. Our results suggest that for some districts (i.e., wealthy districts) teacher salaries’ impact on student performance is something that can be controlled, for other districts (i.e., poorer districts), teacher salary is another variable that shows no relationship to student performance.

The Best Three Years of Your Life: A Prediction for Three-Year Graduation

The 3-year graduation rate is a rarely measured metric in higher education compared to its 4- or 6- year graduation rate counterparts. For the first time in college (FTIC) students to graduate in three years, they must come with certain skills, abilities, plans, supports, or motivations. This project considers two distinct but interrelated ways of using advanced and novel statistical models, the Log-linear Cognitive Diagnostic Model (LCDM) and the Logistic Regression model (LR), to look at both students’ ability to graduate in three years and the characteristics that contribute to this ability. The results indicate that the LCDM is a reliable and efficient statistical model that can provide accurate prediction of students’ ability to graduate early. In addition, student enrolled credit hours in the semester, transfer credit hours, student high school GPA, and student socioeconomic status (EFC) were statistically significant predictors contributing to three-year graduation. The significant interaction between students’ EFC status and transfer credit hours has a meaningfully practical impact on enrollment strategies and institutional policies. Future studies could use the same LCDM model to consider the degree to which these or other characteristics contribute to 4-, 5-, and 6-year graduation rates. Identification of these characteristics could have a policy, student support, and admissions implications. Additionally, the success of the LCDM model in predicting ability could be used for abilities unrelated to graduation, including the ability to pay off loans, succeed in an internship, or give back financially to a university.

The Impact of School SES on Student Achievement: Evidence From U.S. Statewide Achievement Data

After the U.S. Supreme Court restricted the use of race in assigning students to schools, there was a surge in advocacy of school integration based on student socioeconomic status (SES). Benefits of socioeconomic integration have been supported by various studies finding significant effects of school SES on achievement after controlling for individual student SES. This article investigates school SES effects using statewide longitudinal achievement data from several U.S. states. School SES effects nearly vanish after controlling for a student’s prior achievement or, alternatively, controlling for stable differences among students using fixed effects models. The article concludes that large school SES effects often found in cross-sectional studies are artifacts of aggregation and are not a sound basis for SES-based school integration policies.