When institutions use student data, it’s usually internally and to overhaul or make adjustments to campus services year-to-year. Yet, thanks to a younger student body’s familiarity with customized communications based on personalized data, innovative institutions are trying to increase enrollment, boost retention and help place students on a career track with on-the-go data.
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Key Takeaways:
- The University of Kentucky is tailoring on-the-go interactions with its students to increase re-enrollment and boost retention rates ASAP.
- Marist College, a liberal arts college located in Poughkeepsie, New York, has created a portable, open source, predictive analytics model utilizing big data to address the degree completion crisis trending in higher education across America.
- A new survey reveals that students expect institutions to use their personal data to deliver enhanced learning experiences.
- Personalized chatbots now have the capability to become students’ assistants during their postsecondary experience.
(Next page: 3 ways students want colleges and universities to use their personalized data)
How Students Want Universities to Use Their Personalized Data
1. For Enrollment and Retention
A new Ellucian survey, conducted by Wakefield Research, reveals that students expect institutions to use their personal data to deliver enhanced learning experiences. Overall, 82 percent of surveyed students said they believe the use of personal data and information will transform the college experience in 10 years.
Students expect their personalized data will be used by the school to manage their postsecondary experience—from everything like applications to meal planning.
62 percent of surveyed students said they believe institutions should use their personal data to improve their graduation requirements, 59 percent for course selection and registration, and 53 percent for advising. [Learn about more survey findings here.]
One university taking student expectations to heart is the University of Kentucky. In an effort to not only manage, but take full advantage of the increasing volumes of data, the school worked with Dell to create a data model to better predict which students are at risk of not returning in the next term. U of K did this by looking at students with a 50 percent retention rate, then tailoring interaction with those students to increase their chances of re-enrolling.
“Imagine a student coming out of a course and a message appearing on their mobile device asking them, with multiple choice options, how they believe their class just went. Or, based on their enrollment in certain classes or student groups, suggesting weekly campus activities they might like,” described Jon Phillips, general manager for Dell North America Vertical Public Markets during EDUCAUSE 2016. “That’s what the University of Kentucky is doing right now.”
At EDUCAUSE 2014, Vince Kellen, senior vice provost for Academic Planning, Analytics & Technologies at the University of Kentucky, discussed students’ expectation that universities should use student data to help them be more successful.
Video: How the University of Kentucky Improved Student Retention Rates Using Personalized Data
Video: Students Increasingly Expect Universities to Use Their Student Data to Help Them Be More Successful
Marist College, a liberal arts college located in Poughkeepsie, New York, created a portable, open source, predictive analytics model utilizing big data to address the degree completion crisis trending in higher education across America. By utilizing Pentaho’s open-source Business Analytics Platform, Marist students, faculty and staff were able to engage in the research, development, and implementation of an early alert system, the Open Academic Analytics Initiative (OAAI), which is able to identify at-risk students.
OAAI developed, deployed, and researched the open-source “academic early alert system” that predicts which students in specific courses are not likely to complete the course successfully within two weeks of the start of the course. At the heart of the OAAI system is a predictive model that “mines” three historical data sets: student aptitude data, learning management system event-log data, and electronic gradebook data. A rich set of plug-ins and filters to perform various data integration and data mining operations are some of the features in the Pentaho BI platform. These features allow an automated sourcing of data from multiple sources that feed the academic predictive model to achieve accurate scoring. Course-specific Academic Alert Reports are generated, and with this actionable information, faculty can intervene to assist at risk students by deploying one of several interventions, including awareness, tutoring or online educational resources. [Read more about the OAAI and its success here.]
2. For Financial Aid
According to the Ellucian survey, 61 percent of student respondents said they’d like their institution to use their personalized data to help them with financial aid, 58 percent for payment of tuition, and 52 percent for and job applications on campus.
Jami Morshed, vice president of Global Higher Education at Unit4, writes that filling out applications for financial aid, submitting transcripts and recommendations, and navigating the differing due dates, fees and requirements of each school, can be streamlined using a bot integrated with a university’s student database data. For example, during the application process, a bot could send push notifications to students to remind them about upcoming deadlines, missing documents, or improperly submitted data, and would be available 24/7 to answer student’s questions such as “Am I missing any documents for my application?” or “What’s the deadline for submitting the application fee?”
Once tuition, fees, and room and board are confirmed, a bot could even suggest ways in which financial aid can be apportioned and arrange payment according to the student’s wishes. At the beginning of each term, the chatbot could proactively contact the student to confirm if changes need to be made, and could even notify the student about recently announced scholarships or those they now qualify for due to a change in major or academic year. [Read Morshed’s article here.]
3. For Post-Graduation Careers
61 percent of student surveyed by Ellucian said they’d like their personalized data to be used in helping them with their career, as well as 53 percent saying they’d like it to help with their external job interviews.
Already, some Learning Relationship Management systems are using students’ personalized data aggregated from a university’s LMS or database and helping them to create online networks for help and guidance in the post-grad workforce. [Read more about the LRM here.]
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