Optimizing Student Success through Analytics

Fall Planning Retreat

August 13-14, 2012

OVERVIEW

Big Data and Analytics Analytics and Optimizing Student

Success Organizational Capacity for Analytics What do we care about? How are we doing? Focus: Student Engagement Project

StudentsFaculty & staff Institution

Next Steps

Implementing analytics and applying it to make data driven decisions is a major differentiator between high performing and low performing organizations.

Big Data: The Next Frontier for Innovation, Competition and Productivity McKinsey Global Institute. 2012

WHAT WOULD YOU LIKE TO KNOW MORE ABOUT?

Virginia Community Colleges are actively engaged on high schools campuses to advise, recruit and prepare students for successful college entrance.

University of Michigan utilizes Strategic Enrollment Management to identify at risk students and to provide mentoring and support services that have improves the success of these students dramatically.

Structural realignment to eliminate bottlenecks in course and program progressions and unreasonable prerequisites.

Designing curriculum around a full summer semester increased the timely completion for students at BYU-Idaho and University of Northern Texas.

NATIONAL EXAMPLES

Using predictive analytics to shape policies and practices including limiting the number of credits lost during transfer, strict policies on withdrawal and academic progress. Purdue’s Signals program, which has been productized by SunGard, is the best known example of embedded, predictive course analytics. It produces red, yellow and green evaluations of student behaviors in comparison with past behavior of successful students.

Northeastern University has adapted Salesforce.com to create a sort of Learner Relationship Management system for advancing student success.

Sinclair Community College has developed the Student Success Plan (SSP), a case management and intervention software system which it is turning into an open-source product with a community of practice of users at institutions deploying this holistic advising utility.

Arizona State University’s eAdvisor System enables predictive analytics-enabled evaluation of student behavior and learner tracking against norms.

Capella University’s learning objective mapping system provides guidance for each student and is at the heart of their competence-based approach to learning and student success.

Rio Salado’s Student Success Model monitors each student’s progress/success/at-risk indicators; SOS, Status of Students model which took warning levels to a weekly basis using frequency of student log in, site engagement, and pace in completing course as indicators.

Retention systems and services such as those offered by Starfish and EBI/MAPWORKS utilize many LRM-like features.

“NO MORE EXCUSES” Goals of Arizona State

University 2002:• Increasing graduate numbers• Graduation rates• Freshman retention rates• Expand ethnic and economic

diversity Outcomes in 2011:• Increased enrollment 30% in 10

years• Increased minority enrollment

as % of total population by 52%• Increased degrees awarded by

52%• Increased 6-year grad rate by

19%• Increased freshman persistence

to 84% up 9% Solutions:• Comprehensive use of analytics

http://net.educause.edu/ir/library/pdf/ERM1241P.pdf

“We found that by applying analytics through every level of the enterprise we have infinitely more information to allow us to help students become successful.” President Michael Crow

WHAT DO WE CARE ABOUT?

WHAT DO WE CARE ABOUT? Academic performance measures Student enrollment management Student learning and engagement Extended learning and maximizing

opportunities in the metro area Civility and diversity Others

EXAMPLE OF USING METRICS FOR STUDENT SUCCESS Seek to understand the student success

and engagement environment Environmental scan

National benchmarksMnSCU Universities

Inventory of best practices MSU Mankato – deeper assessment of

results Recommendations

PRELIMINARY OBSERVATIONS Campus leadership is committed to

improving student success and engagement. Wide variation exists among the MnSCU

Universities in approaching engagement and student success as well as active and applied learning

Students can be more engaged and more challenged in the classroom

Faculty have a great opportunity to increase active and applied learning in the classroom

Investment and sustainability in faculty, staff, tools, skills and assessment critical

NSSE OVERVIEW Levels of academic challenge Active and collaborative learning Student/faculty interaction Enriching educational

experiences Supportive campus environment

FOUR YEAR BLUEPRINT FOR STUDENT SUCCESS EXAMPLE Pre-Admission First Year Second Year Third Year Fourth Year Transfer

http://www.gvsu.edu/cms3/assets/C70BC1A8-9846-C603-2E5C91853888BC53/BueprintGraphic_9.03.08.pdf

High performing institutions have a “persistent restlessness” about improving student success.

Forecasting,

Risk Analytics

ReportingAnalytics

OptimizationAnalytics

AdvancedDataVisualization

ANALYTICS SOLUTIONS ON THE HORIZON

WHAT SHOULD WE DO NEXT?

NEXT STEPS? Managing the pipeline – Student Enrollment

Management Eliminate barriers to retention and student

success Explore and identify dynamic analytics to

respond early to at-risk behavior Evolve learner relationship management

systems– tools for student success Assess the organizational capacity to

develop improved data analytics Extend student success to life long

learning, career/workforce and life success

TABLE CONVERSATIONS