There is a long-documented problem of inequalities in mathematics education across the United States and in other countries around the world. Previous research suggests socio-economic status (SES) and race play a role — but to what extent and how? Research from Michigan State University scholars answers these questions.
“This study yielded astoundingly interesting results,” said lead author and University Distinguished Professor?William H. Schmidt. “Many scholars who examine curriculum policy and inequalities in mathematics performance conduct research on race and socio-economic status, treated as two separate variables. This study, however, analyzed them both as separate entities and as a combined single variable, which led to distinctly different conclusions.”
The research —?published in the May 2024 issue of?ZDM – Mathematics Education?— explored 17 variables from six national data sets to identify the relationship of race and SES to student performance. The scale of the data sets, Schmidt notes, is rarely available in education research. While other scholars have examined pieces and parts of the data, few have analyzed such a broad sweep of the educational system.
Their findings show SES was “significantly” related to student performance at the system level as defined by the district and school-levels.
Race was not found to be a “significant” factor at the system or district level, but it was statistically significant when examining how race impacts individual student performance within schools.?
“We know race and SES are related to each other,” Schmidt said. “And each is also related to student performance. This study examined the nuances of these relationships under different conditions and from different perspectives. With this study, we have more information, which will collectively help us understand and enact change.”
OPPORTUNITY EQUALS OPTIMIZING SUCCESS
The equation is simple: Students typically do better in math if a school system prioritizes math learning.
The scholars, including Siwen Guo from Renmin University of China in Beijing, and former MSU Research Assistant William F. Sullivan, call this the district’s “zeitgeist.”
“This is one way by which the system data show that SES is statistically related to student performance,” said Schmidt. “If mathematics is emphasized in schools or districts, the entire system — including individual students — benefits. Unfortunately, this emphasis is found more often in higher SES systems.”
HOMEWORK, INDIVIDUALIZED DATA AND STUDENT PERFORMANCE
According to the researchers, the data clearly indicated that the system-level SES was directly related to student performance. “Most striking, however, was the total absence of a statistically significant relationship for race – the percentage of Black students in the school or for the percentage of Black students in the district,” according to Schmidt.
However, race when defined at the individual or student level did have a statistically significant negative relationship to performance. At this point in their research, instead of defining the race of the student, they defined a new variable using the method of intersectionality, which combined the race and SES of the student into one variable. By this definition, there were eight intersectionality groups, or types of students, defined by the combination of race and SES.
When examining the national data sets using the intersectionality groups, the scholars found that some groups spent fewer hours doing mathematics homework than others. For example, they found that Black upper-middle-class students spent 45-50 hours less time than White upper-middle-class students per school year on math homework.
Coupling this with their research on learning opportunities, the researchers stated in their report that there was a “conundrum: the Black upper-middle-class students [were] given the same opportunities to learn but [were] spending less time on their homework.”
At the same time, according to the study, those same Black students had a “lower opinion in regard to the quality of their teachers.” This is an example for only one comparison between two intersectionality groups, but interactions between other intersectionality groupings lead to different conclusions that also require further examination.
In other words, the nature of the negative relationship of race and performance at the student level is much more complicated than people often suggest. Many of the theories that are put forth to explain racial differences are over-simplified and warrant a much more thorough and careful examination, such as the one mentioned above.
What’s next
According to the researchers, teachers, schools and districts should continue to encourage students to persist in their mathematics studies. In schools where math is embraced as part of the culture, students tend to do better.
Yet, Schmidt also acknowledges that while the results presented in the paper are statistically significant, they are also complex and expose politically sensitive social issues. Perspectives from those working directly with students, those who can identify and then offer corrections to challenges, will be why the data could shift in a more positive direction.
“Perhaps, the study can guide us as to where to put our policy focus together with future research to better understand and, as a result, eliminate the inequalities that operate within the U.S. educational system,” said Schmidt.