Using Data Analytics to Analyze Student Progression & Increased Retention & Graduation Rates

Author Information
Author(s): 
Dr. Jeff Stewart, Dr. Marti Venn, Dr. Barry Monk, and Dr. David Davis
Institution(s) or Organization(s) Where EP Occurred: 
Macon State College, Macon, GA
Effective Practice Abstract/Summary
Abstract/Summary of Effective Practice: 

As institutions are being held more accountable for student retention, progression and graduation rates, administrators continue to seek ways to understand what factors are included in the on-going effort to increases rates in all three of these areas. The effective practice shows how one medium sized public institution (approximately 60 00 students) uses data analytics to improve student retention, progression, and graduation rates by driving decision making at the institutional level that pertains to budgeting, programs, and course retention. The practice looks at: * initial evidence * the decisions made based on the evidence * the preliminary results of the initiatives that were put into place * what changes were made based on these data after the implementation of the initiative

Description of the Effective Practice
Description of the Effective Practice: 

An example of the practice using the model of: * reviewing initial evidence * the decisions made based on the evidence * the preliminary results of the initiatives that were put into place * what changes were made based on these data after the implementation of the initiative is illustrated using a pilot project in MATH 1101 – Introduction of Mathematical Modeling where three primary areas of concern were addressed: 1) Attendance & Classroom Engagement 2) Unpreparedness of Students 3) Completion of Homework Seven section of MATH 1101 were part of the project in fall 2010 and 6 sections in spring 2011. Through the redesign of classroom lectures to make them more interactive and a homework management system, there has been an increase in the success rates for those sections and a decrease in withdrawal rates. Elements of the redesign of MATH 1101 have since been implemented in most sections of MATH 1101. It should be noted that this is but one example of how Macon State College is using data analytics for course redesign, program curriculum improvement, summplemental instruction, and to reengage student for degree completion.

Supporting Information for this Effective Practice
Evidence of Effectiveness: 

The evidence that is being used to show effectivness is the successful studnet completion data. The number (and percentage) of students successfully completing MATH 1101 has risen significantly and the number and percentage of students withdrawing from the course has decreased significantly as well.

How does this practice relate to pillars?: 

This practice is one that is scalable and can be done to the extent that resources are available. This practice is focused on learning effectiveness but also addresses student satisfaction as students have a more positive experience and are able to use different learning styles to achieve the same objectives for the course. Additionally, using data analytics provides a strong professional reflection opportunity for faculty who may be stuck in a rut in terms of teaching style or who are not getting the success from students that they are seeking. Using the data to change the way courses and content is delivered to determine what is more effective is a powerful professional development tool for all faculty members.

Equipment necessary to implement Effective Practice: 

Depending on the level in which the use of data analytics is used, very basic reporting from the student information system such as grade distributions for specific classes over a period of time is a starting point. As results are improved and resources are identified, the used of very powerful data analytic software can be implemented which allows an even deeper inspection into the data. For example, one may choose to look at specific sub-groups such as race, gender, remediation needs, etc as possible areas to identify success and then implement targeted initiatives aimed at improving specific group success.

Estimate the probable costs associated with this practice: 

Depending on the level in which the use of data analytics is used, very basic reporting from the student information system such as grade distributions for specific classes over a period of time is a starting point which would cost little as those data are easily obtained. As results are improved and resources are identified, the used of very powerful data analytic software can be implemented which allows an even deeper inspection into the data. For example, one may choose to look at specific sub-groups such as race, gender, remediation needs, etc as possible areas to identify success and then implement targeted initiatives aimed at improving specific group success. These data analytic software packages can cost $100,000 plus, but again provide very powerful tools for using data.

Contact(s) for this Effective Practice
Effective Practice Contact: 
Dr. Jeff Stewart
Email this contact: 
jeff.stewart@maconstate.edu
Effective Practice Contact 2: 
Dr. Marti Venn
Email contact 2: 
martha.venn@maconstate.edu