A group of researchers in Oregon has spent the past several years working on a study to determine whether the no- and low-cost schedule designation used statewide in public community colleges and universities had an effect on student enrollment behavior and whether it has a different effect for historically underserved student populations. We are finally ready to share not only the results of our study, but also our recommendations on how to operationalize these findings on student enrollment behavior through messaging to both faculty and students.
Our results suggest that students are potentially using the no- and low-cost schedule designation to lower the total cost of attendance of higher education in Oregon. Our findings also suggest that historically underserved groups are finding the no- and low-cost designated courses, and that the designation is potentially helping students in these groups get through college with an overall lower cost of attendance. However, the available evidence from the present study does not support the conclusion that historically underserved students had significantly higher enrollment intensity correlated with taking designated courses.
The findings of this study can be used by department chairs and administrators to mitigate impacts for instructors whose employment is precarious. Bookstore managers, registrars, schedulers, and others in support roles can feel confident that their work is improving transparency about costs for students. Agency staff and legislators can use this information to lower the cost of attendance and ensure that students' basic needs are met. We present actionable suggestions for each of these stakeholder groups based on our findings.
By attending this session, attendees will be able to:- Consider whether to adopt/adapt the research method for a similar or larger scale study in their own environment to add to these findings
- Answer with greater confidence questions about the effect of course marking on student enrollment behavior from faculty, staff, and policymakers (with the usual caveats about research limitations)
- Argue for the data-driven recommendations that department chairs, administrators, and policymakers can adopt based on these findings
Link to slides
