Spring 2021 Inside IR

SUNY Online at MCC

By William Dixon

SUNY Online is projected to grow to 1,000 students per program at the state level, helping MCC not only stabilize enrollment but increase enrollment in certain programs.

MCC was selected by SUNY to offer three SUNY online programs, the first of which began in Fall 2019. Over the past three semesters, MCC has seen substantial growth in the SUNY online population in term of headcount and the number ofcredits generated at MCC. (See Figure 1.)

SUNY Online is projected to grow to 1,000 students per program at the state level, helping MCC not only stabilize enrollment but increase enrollment in certain programs. Table 1 below outlines the number of credit hours generated by SUNY Online students.

Figure 1 For SUNY Online at MCC

Figure 1: SUNY Online Student Enrollment

Chart showing increasing SUNY online student enrollment from 20 in fall 2019 to 132 in spring 2020 to 406 in fall 2020

Table 1 For SUNY Online at MCC

Table 1: Credit Hour Enrollment
SUNY Online Enrollment Fall 2019 Spring 2020 Fall 2020
Course Enrollments (1) 80 469 1467
Credit Hours Generated (2) 115 1374 4595
FTE Produced (3) 3.8 45.8 153.2

(1) Course Enrollments equals the total number of courses SUNY online students registered for.

(2) Credit hours generated equals the total number of credit hours generated by SUNY online students.

(3) FTE produced is generated by taking the total number of credit hours generated and dividing by 30.

Fall to Spring Persistence 2020-2021

By Elina Belyablya

There was a similar enrollment decline trend among community colleges across SUNY and the nation.

The overall persistence from fall 2020 to spring 2021 decreased five percentage points compared to the prior spring and went below 70% for the first time in College history. The decreases were especially steep for new students. First-time students’ persistence decreased 9.9 percentage points and transfer ones went down 9.0 percentage points (See Table 2). The decrease of returning and continuing was about three percentage points.

The rhetoric of enrollment and persistence became more critical during the College pandemic life cycle, as spring enrollment continued the downward trend with reduction of 22.8% in FTEs and 19.5% in headcount from last spring. The reduction in spring 2021 enrollment was due to summative effects of COVID-19 Pandemic on the College enrollment: fall 2020 enrollment decline of 12.2% in headcount from prior fall and spring 2021 persistence drop of 5 percentage points.

Similar enrollment decline trend for Community Colleges was confirmed within SUNY (-12.7%) and nationally. At the same time, SUNY four-year colleges and universities did not experience as much volatility (-1.8%) as two-year sector. The reasons for that difference would likely point to the long existing academic risk, equity and vulnerability factors of the serving population. To that affect we can witness lower volatility in some groups within our own institution.

The silver lining is in lower persistence volatility for the continuing students, the ones that had some pre-pandemic MCC experience as well as resilience of continuing.

Thus, white females’ persistence to spring remained flat. (See Table 3.)

For more information, read Spring Enrollments Continue Downward Trend.

Figure 2 for Fall to Spring Persistence 2020-2021

Figure 2: Fall to Spring Persistence by Student Type (among degree-seeking non-grads)

Fall first time student rates. Fall 2014 81% persisted vs 19% dropped. Fall 2015 81% vs 19% dropped. Fall 2016 80% vs 18% dropped. Fall 2017 79% vs 19% dropped. Fall 2018 76% vs 23% dropped. Fall 2019 77% vs 21% dropped. Fall 2020 67% vs 31% dropped.
Fall transfer student rates. Fall 2014 76% persisted vs 24% dropped. Fall 2015 74% vs 25% dropped. Fall 2016 72% vs 22% dropped. Fall 2017 72% vs 24% dropped. Fall 2018 73% vs 24% dropped. Fall 2019 73% vs 23% dropped. Fall 2020 64% vs 34% dropped.
Fall continuing student rates. Fall 2014 80% persisted vs 18% dropped. Fall 2015 78% vs 19% dropped. Fall 2016 78% vs 19% dropped. Fall 2017 77% vs 20% dropped. Fall 2018 77% vs 22% dropped. Fall 2019 76% vs 21% dropped. Fall 2020 73% vs 26% dropped.
Fall returning student rates. Fall 2014 63% persisted vs 36% dropped. Fall 2015 64% vs 35% dropped. Fall 2016 59% vs 39% dropped. Fall 2017 63% vs 35% dropped. Fall 2018 63% vs 36% dropped. Fall 2019 61% vs 36% dropped. Fall 2020 58% vs 40% dropped.

Table 2 for Fall to Spring Persistence 2020-2021

Table 2: Fall to the Following Spring Persistence Rates
Fall Term Fall 2014 Fall 2015 Fall 2016 Fall 2017 Fall 2018 Fall 2019 Fall 2020
Persistance Rate 77.3% 76.0% 75.4% 75.1% 74.5% 73.8% 68.8%

Table 3 for Fall to Spring Persistence 2020-2021

Table 3a: First Time Students of Color Who Persisted
Gender Fall 2017 Fall 2018 Fall 2019 Fall 2020
Male 74.5% 73.3% 72.0% 56.5%
Female 79.6% 75.0% 77.6% 63.9%
Table 3b: First Time White, Non-Hispanic Students Who Persisted
Gender Fall 2017 Fall 2018 Fall 2019 Fall 2020
Male 79.6% 75.3% 78.5% 69.8%
Female 83.3% 80.5% 79.6% 75.4%
Table 3c: Continuing Students of Color Who Persisted
Gender Fall 2017 Fall 2018 Fall 2019 Fall 2020
Male 73.1% 72.2% 73.3% 69.4%
Female 75.5% 75.0% 70.4% 68.3%
Table 3d: Continuing White, Non-Hispanic Students Who Persisted
Gender Fall 2017 Fall 2018 Fall 2019 Fall 2020
Male 76.7% 80.8% 79.9% 74.7%
Female 79.0% 77.9% 77.8% 76.8%

Top Initiatives that Impact Persistence

By William Dixon

Practices that have a significant impact on student persistence include:

  • awarding financial aid
  • having students attend learning center appointments
  • meeting with their advisor.

Beginning in Fall 2017, MCC has used the CIVITAS Impact tool to identify what impact initiatives have had on student persistence. These “Impact” reports compare students who participated in the initiative to students who look almost identical to them in terms of persistence scores but did not participate. This creates one of the strongest research designs in statistics, called a quasi-experimental design, and has been used in peer-reviewed research many times.

Analysis of MCC’s top initiatives indicate common practices that have a significant impact on student persistence and could be used for future resource allocation. The practices include; awarding financial aid to students, having students attend learning center appointments, and meeting with their advisor. Conversations with CIVITAS confirm that these practices have had lifts in persistence for almost every school that has measured them. Our results show the overall lift in persistence but each initiative may impact certain populations more than others. A complete Impact report is available for each initiative listed here and can be requested from the IR office.

Table 4 for Top Initiatives that Impact Persistence

Table 4. Top MCC Initiatives and the Lift in Persistence
Initiative Lift in Persistence Lift in Persistence
Student Support Services (SSS) 17.8%
CARES Act Funding 17.2%
CircleIn 13.5%
Spring 2020 Students Receiving EOP 11.5%
Received APTS funding – Part Time Students 9.5%
Scheduled and Attended 2 or More Advising Sessions 9.2%
Received a Starfish Kudo 9.0%
Attended the Academic Foundations Learning Center 8.9%

MCC Digital Access Survey Results

By Mary Ann M. DeMario

Windows 10 is the operating system students need to best access MCC platforms.

In December 2020, a link to MCC’s Digital Access Survey was emailed to 11,173 students. We received a 6.1% response rate, which gives us a margin of error of ±5%. This means that the results can be generalized to the fall student population.

For Student-Parents, access to technology is critical for their school-age kids as well as themselves. As shown in Figure 3, 52% of Student-Parents have school-age kids. But that may be as high as 72% due to the unknown age groups.

The key findings are that:

  • 96% of students owned a device they could use to access their coursework remotely. However, Pell-eligible students, students of color, and Single Mom Learners had lower levels (94%, 93%, and 88%, respectively) of access to devices.
  • 59% of students had access to a PC with Windows 10, and nearly half of students owned a smart phone.
  • 88% had reliable high-speed internet access at home. Pell-eligible students and students placed in TRS courses were less likely (82% and 79%, respectively) to have it.
  • 59% of students without a device reported being able to come to campus to use MCC technology and Internet. The subgroups who were less likely to do so were Pell-eligible, female, and Student-Parents (52%, 55%, and 45%, respectively).
  • 60% of students without a device reported being able to come to campus to take a proctored exam. The subgroups who were less likely to be able to do so were Pell-eligible and Student-Parents, most noticeably Single Mom Learners (56%, 50%, and 44%, respectively).
  • One-third of students had problems accessing the programs and applications they needed for school, such as Blackboard and Zoom. More full-timers than part-timers (34% vs. 26%) had problems.
  • Only 15% of students said their access to technology negatively impacted their schoolwork. The groups more likely to report a negative impact were males, first-time and continuing students, and students who were college ready in math (17%, 17%, 18%, and 19%, respectively).
  • 91% of students had a webcam, but fewer part-timers (86%) had one.

Students’ typed-in comments shed additional light on technology issues. For example, among students who don’t have Internet access at home, the most common way they access the Internet is by creating a hot spot using their smart phone. Students also reported frequent problems with Blackboard and Zoom.

Figure 3 for MCC Digital Access Survey Results

Figure 3: Age Groups of Student-Parents’ Children

Venn diagram of age groups of student-parents' children. Ages 5 and younger only 29%. Ages 6 to 18 only 33%. Both age groups 19%. 20% of ages are unknown.

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