Numbers Talk…No. 5: Class size, GPA and persistence – Is there a relationship?

Click here to download a PDF of this report

It is commonly believed that smaller class sizes are positively related to stronger student performance.  While it is not clear what the optimal class size should be or if it varies by the nature of the course material, intuitively, there are several reasons that argue for the general truth of that statement, e.g.,

• Each student gets more attention from the instructor.
• The pace of the class can more easily be moderated to accommodate fewer students.
• In a more intimate environment, students are likely to be less intimidated and more likely to ask questions/share perspectives.

We looked for evidence from our data to support – or not – this relationship.  Information from seven programs of study averaged across available data from Fall 2005 through Summer 2009 was reviewed.   Though they were not randomly selected, these programs do represent a diversified set of courses.

Across programs, no one program had more than 36 students in any one course.    For this analysis, the distribution of students was arbitrarily trisected such that segments with up to 12 students are compared to segments of 13 to 24 and 25 to 36 students, as appropriate (i.e., not all programs had 36 students).

Additionally, independent study courses were deleted from the analyses.   Independent study courses by definition have a very small number of students with individualized study plans which may bias the more general look at the effect of class size.

Four metrics were calculated for each class size segment within each program:

• Average GPA,
• The percentage withdrawing (student or instructor initiated),
• Percentage success (the proportion of students who received a grade of A, B or C),
• Persistence rate (proportion of students who completed the course regardless of grade).

The number of courses in each class size segment is also noted.  All details appear in the tables at the end of this analysis.

The specific hypotheses we are testing with this analysis are these:

• Across programs, smaller classes (those with 12 and fewer students) are associated with higher average GPAs than classes with more than 12 students.
• Across programs, smaller classes (those with 12 and fewer students) are also associated with higher success rates and higher rates of persistence than classes with more than 12 students.
• Across programs, smaller classes (those with 12 and fewer students) are associated with lower rates of withdrawal than classes with more than 12 students.

The following tables are color coded so that the outcomes are apparent.   The blue shading indicates values decline as class size increases.   The yellow shading indicates values increase as class size increases.  (Note:  These metrics tend to be intercorrelated.)

Across the aggregate of courses within each of the 7 programs…

• GPAs in smaller classes were highest in 5 of the 7 programs.
• Success rates in smaller classes were highest in 6 of the 7 programs.
• Persistence rates in smaller classes were highest in 7 of the 7 programs.
• Rates of withdrawal are lowest in smaller classes in 7 of the 7 programs.

This is a compelling set of evidence in support of the hypotheses.   However, not all of these relationships are perfectly linear when all of the data are reviewed.

• For example, within the Sciences program, persistence rates decline when the smallest class size (12 students or less) is compared to the next class segment 13 to 24), but increase when the class segment of 13 to 24 is compared to the largest segment of 25+.
• All of the metrics calculated for the Business Administration program also show non linear patterns.

It is not clear why the patterns deviate for these two programs.  I welcome any discussion around these anomalies; insights are often hidden within them.

Earlier blogs and discussion confirm the belief that persistence and retention are positively related, but it is unclear how strong that relationship is.  We can only suggest (as we have before) that increases in persistence will lead to increases in retention.

In this data set, the average increase in persistence when class sizes of 12 are compared to those of 13 to 24 is 3.9 pts.  While there is no guarantee that retention would increase 3.9 points with class sizes of 12 or less, a cost-benefit analysis would determine what it would cost to reduce the average class size and what increase in retention rate would justify the expenditure.

Submitted by Cindy Schersching, PhD, January 16, 2010

Key metrics by class size across select programs (Fall 2005 – Summer 2009)

Legend:  Blue shading indicates values decline as class size increases.   Yellow shading indicates values increase as class size increases.

*This definition of OST includes BUS 151, CTS 125, CTS130, CS 165 and excludes OST 080 AND 131 per the program head.

Early Alert … End-of-Fall 09 report

We’ve published an end-of-term report for our first semester pilot of the Early Alert system.  Click here, or on the image above to access the blog page and the report.  (or follow the pages over on the right side of this page).

Numbers Talk…No.4: How are we doing?

It is frequently useful to benchmark key metrics to a known universe of similar organizations.

Benchmarking can tell us if we are moving in the right direction, how much ‘head room’ we have to grow, and, alternatively, whether there are areas that need more resource to bring performance up to par.
A second benefit of using benchmarks is that – with some assumptions – we can infer performance numbers that we are unable to generate.
For this exercise, we will use summary numbers published by Noel-Levitz, a respected agency with known expertise in educational/institutional research, and compare them to similar numbers generated for Carteret Community College (CCC). We will begin with the comparison of retention and the percent of hours completed relative to the number attempted. CCC metrics are run on the same sample definition and time frame as the benchmark numbers.

Retention Rates and Percentage of Hours Completed
Base: Cohorts, first time, full time, degree seeking

Retention Rates Percentage of Hours Completed divided by Total Hours Attempted
Noel-Levitz 2-Year Public Institutions Carteret Community College Index:
CCC/

Noel-Levitz
Noel-Levitz 2-Year Public Institutions Carteret Community College Index:
CCC/

Noel-Levitz

2007-2008 55.8% 59.3% 106 75.0% 77.6% 103

CCC compares quite favorably with these key national numbers; we are in the top half of the sample distribution of 2-year public institutions.

Noel-Levitz also generates a persistence rate for 2-year public institutions. For this time period and sample definition, it is 71.3%. For a variety of reasons, we are unable to get a comparable number for CCC.

The response to the last blog regarding persistence and retention rates suggests the relationship between these two metrics is likely a strong – though not perfect – positive one. Noel-Levitz also concludes that ’ term-to-term persistence benchmarks within a given academic year are natural predictors of year-to-year retention rates for a cohort of students. As such, these benchmarks serve as early indicators of attrition, facilitating intervention’ (2009 Noel-Levitz, Inc. • Benchmark Research Study Conducted Fall 2008—Mid-Year Retention Indicators Report).

Using these assumptions, a conservative reasonable estimate of persistence suggests CCC is also in the top half of the distribution.

When 2008-2009 estimates of these same metrics become available, we will be able to re-apply/re-test our assumptions and update these comparisons.

Submitted by Cindy Schersching, PhD, December 2, 2009

IDEC

Carteret Community College’s Title 3 was generous enough to pay for Tammy and I to go to the 2009 IDEC South Regional Conference! It took place Oct 14-16 and was hosted by Meredith College in Raleigh.

The title was “Text, Twitter & Podcast: Reaching the Millennials”. In order to cover more territory, Tammy and I split up and attended different presentations whenever possible.
One of the workshops:
Weaving Together Stories: Making History Relevant through the Design Cosmology Blog.. This was presented by Patrick Lucas of UNC-G

This presentation was about combining more than one course. Professors working together. The students were expected to blog the whole 16 weeks. This was a great exercise in students working together, and learning to talk out loud about Design! According to Mr. Lucas, by the end of the 16 weeks…Major conversation between students! He felt the blogging enabled them to also talk out loud when they were together in lab, near the end of the semester. They did great on their oral exams/presentations.. Blogging was very effective here.

Millennial Students..

Service Projects:

“Rebuilding Pitt County”

Millennial students seem to be very into community service compared to other groups (baby boomers for example). Millennials are often called Boomerang kids, due to the fact that they move back home after college. Yikes! They seem to have more of a spirit of volunteerism, and do not expect to have just one job over their lifetime. They love working in groups/collaborating/teamwork.

This was about a group of students working with Habitat, and having the opportunity to interact with real clients. It gave them opportunities for scholarly writing & for presenting their project.

Furniture for the Millennial Student

“Text, Twitter, Podcasting”… Millenials are adept at filtering information and making snap decisions.. multi-tasking.
A really good book that was recommended during this presentation, “Shift Happens” by Fisch. We’ll have to check it out!
Studies have shown that if students and faculty are attracted/comfortable with spaces used for learning.. it actually raises the retention rate. This is why Steelcase is focusing on today’s Millennial student and their way of learning/communicating (texting, computers, social interaction, groups..) Also, important to note, is that learning takes place everywhere (hallways, lobbies, student centers..).
Steelcase website:
www.beagreengiant.com
This presentation was made by Emily Walser. She is coming to CCC to speak to IDesign and anyone else interested about Steelcase, Inc. on Nov 23rd at 1pm.

In Conclusion..

After attending the SouthEastern Interior Design Educator’s Council Conference, it has been made clear that Carteret Community College is on the cutting edge in Distance Learning. The title of the Conference, might have been a bit misleading. There were some positive mentions regarding blogging (like the workshop by P. Lucas), and his combining of classes/blogging/presenting was an awesome idea..and folks discussed their use of Blackboard, but not to the extent we had anticipated. Many folks/educators out there are still resistant to on-line teaching, (as many of us were several years ago). The Steelcase representative stressed the importance of accomodating the Millennial student and the way they learn (on-line, groups..) She was a good speaker. It was well worth the trip!

CCC Online Tutoring Update

Although slow to develop, CCC’s online tutoring service is providing meaningful assistance to students in a variety or courses, from math and algebra to English, psychology and sociology and science courses. Here is a comment from a distance learning student this semester who was having difficulty accessing a computer CD that accompanied her textbook:
“I am amazed of how wonderful you and Mr. Brooks Pace are to us. Thank you for be here for us at anytime we need help.  It can be a stressful here at home sometimes by ourselves when we need help. You guys are our release — thanks!”

One of the best things about the service is that students who have been helped one semester are returning for help with their other course work, and they are referring other students. A few instructors are also directing their students to the Online Tutoring Service for assistance, which serves both the students and instructors.

Whether responding to e-mails or Blackboard Discussion Board postings, we try to be prompt in our responses and to provide meaningful feedback to enhance the students’ understanding of the material they are learning, and that seems to be working as evidenced by this student’s comment:

“I just wanted to thank you again for your help with my essay. I got a 97! I learned a lot from your tips too, so thank you again.”
We want to facilitate learning — not do their work for them.

We also make ourselves available by phone, if necessary, and have even met with a few students face-to-face. In addition to the tutoring, the Blackboard site offers resources and links that help some students “self-serve.”

When necessary, we will e-mail instructors to be sure we are clear on what their expectations are for their classes or a particular assignment. We would like to have even more collaboration with CCC faculty, whether it be to help their students fine-tune their work or spend some extra time with those who need some remedial help.

We all know that many CCC students are juggling, school work and families, so online learning is the best option for their education. It does, however, limit their face-to-face access to instructors during their office hours or to campus academic support. As more and more classes are being offered online and more and more students are taking online courses, the benefits and use of online tutoring is likely to grow.

Lisa Taylor-Galizia
Carteret Community College
Adjunct Instructor

The CCC Online Tutoring Service is a Pilot Program Supported and Funded by Title III.

DL at CCC – Hitting the Ground Running!

We are now 3 weeks into the Fall semester and the Distance Learning Team in working on a variety of professional development initiatives, in addition to making sure all online courses at CCC are meeting the Quality Assurance Standards we established last year. We have cross referenced a sampling of our online courses and I must report it is good to see how all the Blackboard training has paid off and so many of our faculty are implementing more creative and innovative instructional design strategies. Our Title III funding and support has played such an integral part in the progress we’ve made over the past 3 years.

Our fourth DL Pioneer team has been selected and we had our kick-off meeting last Friday. We have an excellent team made up of both faculty and staff and they’ve all made commitments to retool and upgrade their online courses, attend professional development activities in their disciplines and essentially take their knowledge of online learning and distance education to a higher level in the next year all made possible by Title III funds. Our staff members on this team will be exploring and implementing new and creative ways (blogging, Youtube, facebook, twitter) to work with our student in the online environment

As Vice President of the NC3ADL Eastern Region I’m also in the process of coordinating a Regional DL mini-conference/workshop for Friday, November 6th here at CCC. Due to travel restraints across the state it looks like there will be no NC3ADL conference this year so we are doing a series of regional conferences. NC3ADL will pay for lunch and I’m going to look to our DL Pioneers from Phase 1-3 to assist with it and have phase 4 attend. The following is a rough outline for that regional conference/workshop.

Workshop Overview – Two Tracks  Friday, November 6, 2009 9:00 – 4:00

2 tracks in the morning 9:30 – 10:30 and 10:45 – 11:45
Lunch 12:00 – 12:45
2 tracks after lunch
1-2 and 2-3 (Optional Track 3-4 on Dl Assessment)

1. Moodle Basics
2. Podcasting for the Technically Challenged
3. Best Practices for Online Teaching
4. Learning Object Repository
5. Social Networking as a Teaching/Learning/ Marketing Tool
6. Blogging for Beginners
7. Incorporating Itunes U and You Tube in your online courses.
8. DL Assessment with Don Staub

My constant goal is to make our online classes every bit as viable, interesting and dynamic as our traditional classroom lectures and labs. Thankfully there are a host of new and powerful communications tools that are making it easier and less time consuming for our faculty to do this. Carteret Community College has a Title III grant resources to help us implement our various professional development initiatives and put these tools in the hands of our faculty so they can take their online teaching to a whole new level of technical and pedagogical excellence.

Numbers Talk…No. 3: Retention and Persistence – Is there a connection?

Retention rates are the proportion of students who graduate or return to their program the following semester.  Usually, retention is calculated from Fall to Fall, but Fall to Spring  metrics can be generated.   Retention is a key metric used to compare college performance throughout the US.

Persistence refers to the proportion of students who complete a course.

Typically, retention rates are reported for programs; persistence is reported for courses.

While it makes intuitive sense that persistence would be related to retention, this is challenging to prove.

Therefore, in the true spirit of blogging, I’d like to entertain all ideas regarding the hypothesis that these measures are related.

• If you don’t think they are related, let me hear why.
• If you think retention and persistence are related, let me know that and how strong you think the relationship is (i.e., if you know one measure, you know the other; persistence explains only part of retention-other factors are more important, etc.)
• And if you think there is a relationship, how can we show it?

Why would a connection between retention and persistence be useful to demonstrate?

When we know which relationships have the most influence on retention, we are more likely to influence it and therefore, improve retention rates.  Conceptually, persistence is similar to retention in that the student completes something.

Further, persistence may be easier to influence than retention since it is measured at the course level.

Both are important metrics.   If retention and persistence are positively related (i.e., as one improves, so does the other), efforts to influence one metric will positively impact the other.  This will enhance our understanding of both program and course level performance using the tools already in place and give us confidence that we are using our resources in the best way.

Submitted by Cindy Schersching, PhD, August 20, 2009