UW-Madison’s Xueli Wang is the author of a groundbreaking research article examining community college course-taking patterns that contribute to effective academic pathways for transfer-aspiring students in science, technology, engineering and mathematics (STEM).
The article, which is already available online, is titled “Course-Taking Patterns of Community College Students Beginning in STEM: Using Data Mining Techniques to Reveal Viable STEM Transfer Pathways.” It will appear in the August issue of Research in Higher Education.
Wang is a faculty member with the School of Education’s Department of Educational Leadership and Policy Analysis, and is an affiliate of the Wisconsin Center for the Advancement of Postsecondary Education (WISCAPE).
Earlier this year, Wang’s study received a Charles F. Elton Best Paper Award from the Association for Institutional Research (AIR)
. These awards, the AIR website notes, "celebrate the scholarly papers presented at the AIR annual conference that best exemplify the standards of excellence established by the award’s namesake and that make significant contributions to the field of institutional research. The purpose of the award is to promote scholarship and to acknowledge that AIR members make a wide variety of scholarly contributions to the field, ranging from theory to practice."
In her study, Wang explains that she used national postsecondary transcript data from the National Center for Education Statistics -- and data mining techniques rarely adopted in higher education -- to more closely examine course-taking patterns of beginning community college students enrolled in one or more non-remedial STEM classes during their first year of college.
Wang notes that she discovered some interesting course-taking patterns among these community college students that are linked to their upward transfer pathways in STEM.
The study reports it is “intriguing to note that, among STEM transfer students, despite the inevitable math-learning path, math course-taking during the very first term does not appear to be the most frequent course-taking pattern. Instead, the most viable course-taking trajectories contributing to STEM transfer, by and large, feature a pattern that first introduces ‘likely transferable’ STEM courses during the first term (i.e., to ‘get their feet wet’ first), followed by math exposure during the subsequent terms.”
“This result is different from the conventional wisdom viewing math as the gatekeeping courses and that students have to first pass their math classes in order to succeed in STEM,” says Wang, adding that there are numerous other findings in the paper -- including some disparities based on gender and age of community college students in their STEM pathways.
Wang’s paper concludes by explaining: “Despite the importance of understanding the connection between course-taking patterns and transfer outcomes in STEM, remarkably little empirical knowledge exists to illuminate viable STEM pathways for transfer-aspiring students. This study set out to fill that gap by applying data mining to transcript records, resulting in new insights to inform future research in this area. The knowledge produced by this study can also assist educators and policymakers in improving curriculum design and program offerings and strengthening intercollegiate course and program articulations. Such collaborative efforts will help cultivate social and organizational capital among 2- and 4-year institutions, and facilitate effective and efficient STEM educational pathways for interested community college students.”
To learn much more about this nuanced topic, check out Wang’s entire research article via this link