Introduction One of the many definitions of Predictive Analytics says that it “describes a

range of analytical and statistical techniques used for developing models

that may be used to predict future events or behaviors1” For some time

now, retailers like Amazon and Tesco have leveraged predictive analytics to

acquire an amazing depth of customer understanding and deliver

personalized propositions. Automotive giant BMW is using it to identify and

fix vulnerabilities before putting new models into production. Financial

institutions are leveraging this technology for purposes as diverse as

improving cross-selling effectiveness and mitigating risk. For the education

industry, a comparative latecomer to this field, it is in student retention that

predictive analytics will find its biggest role.

The challenge of churnMinimizing dropout ranks among the top priorities of education providers today. Globally, the problem of youth unemployment is being exacerbated by the

absence of critical job skills. The only way to address this talent gap is by

improving the delivery of higher and tertiary education. However, to achieve

great learning outcomes, educational institutions must not only provide

course content and teaching of high quality, but also ensure that every

student completes the program. When students drop out of their courses, it

not only impacts the employable talent pool but also wastes the

considerable resources that were spent to enroll them. Just to see things in

perspective, consider that in 2012-13, private institutions in the United

States offering four-year programs reported a median spending of US$

2,433 per student recruitment2; several for-profit universities ended up

spending more than twice that amount3.

A post graduate from IIM, Lucknow

with about 20 years’ experience

Arvind, has spent the last 10 years

in leadership roles advocating

technology in Learning, Training

and Assessment with customers

across the globe.

About the authors

Predictive Analytics for Student Retention

Arvind ThothadriVice President – New Initiatives

Co-founder of MeritTrac Services,

India’s largest assessment

company that develops and

delivers over 2 million online and

paper assessments each year,

Mohan drives development and

innovation on EduNxt Learning

Ecosystem.

Mohan Kannegal Head - Learning Solutions Group

Small wonder then that minimizing dropout ranks among the top priorities of

education providers today. As schools, universities, private educational

organizations and corporate entities take a number of steps – ranging from

a more selective enrolment process to student counseling – to improve

retention, they are finding a valuable source of support in predictive

analytics.

Institutions can employ analytics at various stages of the student lifecycle to

manage dropout. Information that is collected at the admissions stage, to

determine student eligibility such as financial background and academic

proficiency, can be later revisited to identify students that need special

attention and support. However, education providers will maximize

outcomes only if they deploy predictive analytics throughout the course of

engagement.

The role of learning management platforms The choice of learning management platform is critical because of its role in

collecting student data & predicting graduation rates. While most platforms

manage the student lifecycle from end-to-end (enrolment through

certification) quite efficiently, they don’t necessarily have the same analytical

prowess. EduNxt is a platform with comprehensive, proven analytics

capability. EduNxt Analytics evaluates and monitors, Student Performance,

Content Quality, Course Health and Student Engagement to provide user

institutions and enterprises with key insights, which are extremely relevant

to student retention. A student’s performance in terms of the number of

hours spent on a course versus the class average and minimum required to

pass, is one of the factors that determines test scores and likelihood of

course completion. EduNxt Analytics draws attention to other such red

flags, like a higher than average bounce rate for a particular topic, poor

participation or performance in assessments and interaction sessions, and

most telling of all, flagging engagement. Some of the factors which seem to

greatly influence a student’s decision to continue with the program include

the time spent on the platform and the “Recency Effect” produced by the

results of the last semester exam.

Choosing a platform with

comprehensive, proven

analytics capability.

The Right Analytical ModelEduNxt Analytics is driven by a robust modeling methodology and engine,

which studies data gathered from various systems in the ecosystem to

identify influential factors in student retention, such as course delivery,

content, student engagement and student performance. This resolves a

major challenge faced by institutions, whose data usually rests in multiple

departmental and transactional silos – Student Information, Learning

Management, Examination, Results Consolidation, and Helpdesk systems

etc. – making it difficult to see a holistic view of the problem. EduNxt

Analytics overcomes this by providing a single view of all student information

along with access to historical data.

Further, the platform provides clear insights and actionable points to

empower educational institutions and their faculty to make timely

interventions.

ConclusionOne of the biggest goals of education providers is to maximize learning

outcomes for their students. To achieve this, institutions must ensure that

students go the distance and complete the program. Program dropout not

only diminishes

learning outcomes but also wastes the resources invested in student

enrolment. Predictive analytics plays a crucial role here by identifying

students at risk early and suggesting remedial courses of action at every

stage in a program.

The EduNxt Learning Ecosystem has worked with educational institutions around the world to transform the way they manage student retention and deliver value to each student.

EduNxt is the Unified Learning Solution from Manipal Global Education

Service Pvt Ltd. EduNxt is the backbone through which online learning is

driven across the various Educational institutes in the Manipal ecosystem.

EduNxt plays a key role in learning and assessments during the entire life

cycle of a student from enrolment to graduation. A very robust ( over

250,000 users ) and easy-to-use platform that is mobile enabled, it comes

With the help of EduNxt

Analytics, Sikkim Manipal

University, the largest

privately owned distance

education provider in India

was able to identify

students at maximum risk

of dropping out with 96%

accuracy.

with top end analytics that facilitate key stake holders from students,

teachers and administrators to leverage and take pro-active remedial

action.

1. http://www.techopedia.com/definition/180/predictive-analytics

2. https://www.noellevitz.com/papers-research-higher-education/2013/2013-cost-of

-recruiting-an-undergraduate-student-report

3. http://www.eduventures.com/wp-content/uploads/2013/02/Eduventures_Predictive

_Analytics_White_Paper1.pdf

References :

Get in touch with us!

Mr. Arvind Thothadri at arvind.thothadri@manipalglobal.com