Another Paper for the Retention Conference

**Update - This has been approved at the first stage. Once we write the paper, we will know if it is to be published.

Once again, any help would be greatly appreciated :)

We’re Up 17% - What Now?

Abstract:

From 2010 to 2017, we have raised our developmental education success rates at Moraine Valley Community College by more than 17%, while lowering our withdrawal rates by 30%. More importantly, we have done so while we simultaneously increased the acceleration of some of our programs and created bridge courses, often skimming the stronger students off of our upper-level courses. Initially, we utilized global data (i.e. our success rates, the success rates of our students at the next levels, our attendance rates, our grade patterns, etc.) to suggest policies and curricular alignment. At this point in the process, we are attempting to turn to more local data, focusing on individual performance and the appropriate resources we can provide our faculty and staff. This paper will address the strategies we developed to address our low success rates, as well as the next steps we plan to take in our continuing improvement process.

Description and Learning Outcomes:

In the course of the past seven years, we have raised our developmental education success rates at Moraine Valley Community College by more than 17% (i.e. those students earning grades of A, B, or C, as opposed to D, F, or I) and have lowered our withdrawal rates by 30%. It has been a systematic, “soft data-informed” process. We began by confronting our general retention data and reviewing our policies and procedures. For instance, in order to introduce the possibility of adopting a departmental attendance policy, we first conducted a survey with our faculty asking them to code all their assigned F grades and to note which instances were due primarily to attendance. Our faculty reported that more than 70% of the F grades we had awarded were due to low attendance. This began a gradual implementation of data into our analysis, planning, and evaluation processes.

As we began to work on our retention plan, we were faced with an impending migration from COMPASS to ACCUPLACER as our primary placement test. We capitalized on this challenge by analyzing all of our available data in regards to student placement, matriculation rates, and future success. In doing so, we discovered large overlaps in curricula between academic levels, severe compression of grades in some courses, and the “over-success” of our “A and B” students moving to credited coursework. As a result, we have developed new metrics to track the efficacy of our placement instruments, how well we transition students from lower levels in the curricula, and how well they persevere into and through their credited sequence.

While evaluating our programming, we discovered that we suffered from some unusual side-effects of our efforts to be innovative: We began to develop so many interventions that we lacked the ability to assure that the right student entered the right intervention (RSRI- Right Student, Right Intervention). Subsequently, we began to work with advisors and other stakeholders on campus to help delineate our offerings and to ensure students would know if they were a right fit for a particular type of course or intervention.

As a result of the analyses we conducted, we collaboratively designed an attendance policy, reevaluated our curricular transitions, worked to ensure students had their textbooks and required materials, and involved other critical stakeholders on campus in order to create a more consistent and visible pathway for our developmental students. Our efforts have led, in small part, to the creation of enrollment and grade dashboards with our Institutional Research department, as well as an ongoing relationship that has led us to many other questions, challenges, and resources.

Finally, we are preparing to move from larger data sets to local indices to share with instructors at the classroom level. Doing so should provide our faculty with the appropriate feedback for course improvements that will ensure that we maintain and raise our improved success rates.

Learning Outcomes – Participants will review their own transitional and longitudinal data process; Participants will learn about new retention and perseverance metrics.