Math Infusion in Agricultural Education and Career and Technical Education in Rural Schools

Spatial Inequities in Advanced Placement® STEM Success: Investigating Rural Disparities in Examination Results

“…Further, Byun et al (2012) found that rural students were significantly less likely than both urban and suburban peers to take rigorous coursework. Similarly, studies have also shown that rural students have fewer opportunities to take advanced coursework in STEM relative to their differently-located peers (Anderson & Chang, 2011;Irvin et al, 2017;Saw & Agger, 2021;Wolfe et al, 2023). Specific to AP ® examinations, Mann et al (2017) found that when enrolled in an AP ® course, rural students are least likely to sit for the exam, and of those who do test, they take less exams, on average, than their differently-located peers (Table 1).…”

Getting Students to (and Through) Advanced Math: Where Course Offerings and Content Are Not Adding Up

“…3 Disproportionately fewer students of color and students living in poverty are enrolled in algebra I (Patrick, Socol, and Morgan, 2020;Stein et al, 2011). Rural students, too, are more likely to begin high school with less mathematical knowledge than their peers (Anderson and Chang, 2011). Because of the central position algebra occupies as "a gatekeeper to higher mathematics" (Stein et al, 2011), differential access to algebra I between student groups has led some states and districts to experiment with more extreme approaches to "leveling the playing field," including promoting algebra I for all students in grade 8 (e.g., California and Minnesota) or universally delaying algebra I until grade 9 (e.g., San Francisco Unified) (Sawchuck, 2018;Jacobson, 2008).…”

A Within-Group Approach to Ensemble Machine Learning Methods for Causal Inference in Multilevel Studies

“…Algebra courses are mathematics courses offered in U.S. school systems, and prior studies have advocated policies that encourage students to take algebra prior to entering high school (Rickles, 2013). These studies also found that school-level characteristics such as school location, school composition, and school processes play a key role in students’ mathematics course-taking and their performance on achievement tests (Anderson & Chang, 2011; Cogan et al, 2001; Opdenakker & Van Damme, 2001). Unfortunately, the ECLS-K data did not measure all possible school-level confounders, such as school’s funding for math education and school principal’s emphasis on STEM education, and estimating the treatment effect consistently becomes a challenge.…”