Personalization and Collaboration: To Find Student Success, Get Student Ready | | Discourse Analytics

To Find Student Success, Get Student Ready

Personalization & Collaboration in Higher Ed

Digital Transformation in Higher Ed

The student is higher education’s raison d’être. That means we have to ensure that the institution is student -ready, rather than expecting students to be college -ready. As described in Top 10 IT Issues for 2019 – The Student Genome Project, being “student ready” though means, amongst other things, the ability to activate technology and gather insights to meet student needs at every turn.

Compelling students to take action, though, can be a significant challenge. Personalized communications – right message, right channel, right time – can provide useful prompts that help move students through the inertia of university and academic life, and help them complete the necessary milestones to transition along their life-cycle journeys. But, the “right” part of that message is more than demographic- and trigger-based text engagement.

In the above-referenced Top 10 report in the Educause Review, Tammy Clark (VP of IT, University of Tampa), Carlos Morales (President, TCC Connect Campus), and Jerry Slezak (Director, IT Support Services, Mary Washington) call out the importance of cross-functional collaborations between and among all functions and departments within the University, including faculty, advisors, course designers and admissions. IT or Student Services are no longer siloed domains. Simply put, the quality of the technology solutions is paramount as institutions seek to support every phase of the student life-cycle:

“If even a single department serving students provides a suboptimal technology experience, that can have an effect on overall enrollment and retention levels. “

Collaboration and breaking down silos must now become the mission focus, rather than just deploying additional tech. The report “We Shoulda Known: Lessons for the Future from the Past”, Gregory Jackson (MIT Educational Counselor & Fortium Partner), Klara Jelinkova (VP IT & CIO, Rice University), Joseph Moreau (Vice Chancellor of Technology & CTO, Foothill-Deanza Community College District) and Jenn Stringer (Chief Academic Technology Officer & Assistant Vice Chancelor, University of California, Berkeley) highlights the importance that new solutions integrate with the systems that are already deployed across the school, and align with the specific business missions of the organizations they are enabling.

The report notes that institutions need to holistically evolve to support the personal needs of their students – their consumers – much in the same way that commercial organizations like Amazon and McDonald’s do. Today’s students are technology natives, and engaging with them on their platforms and devices of choice is of paramount importance to the institution. The result is that control over device usage is more dispersed; it can’t be mandated from the top down. And, institutions must support mobile solutions and other bring-your-own technology models that put control into the hands of the student.

Lessons from the Commercial World

McDonald’s $300 million acquisition of Dynamic Yield, a personalization and decision logic platform, was but the latest personalization investment to leverage predictive & prescriptive analytics to drive better business outcomes. The move puts McDonald’s in the seat to be the world’s largest personalized retailer,moving beyond “people who bought this also bought that”, and suggesting menu items based on data related to the weather, time of day, and trending items. Both companies, and many others investing billions of dollars in marketing technologies like CRM’s, DXP’s and CDPs, seek to move far beyond common purchases, to understand the motivations, mindsets and desires of their customers, in an effort to place the next best product in front of the appropriate customer, via the best channel, and at the best time.

But the real key to unlocking the value of the consumer and behavioral data captured in the enterprise is the ability to activate recommendations through consumer touchpoints. For Amazon, its technology-first approach to everything has allowed it to grow through personalization. The value McDonald’s sees from Dynamic Yield is an accessible API that can enable the fast food giant to activate recommendations coming from Dynamic Yield without significant efforts.

Efforts to improve Student Success will come much more easily as universities and institutions learn from and integrate some of the lessons from the commercial world.

Personalizing in Higher Ed with Prescriptive Analytics

Technological business needs now cut across all departments. And, siloed business operations are no longer “good enough.” All departments need to align with the central missions of technology innovation and specific student outcomes. According to a report from NASPA and the Association for Institutional Research entitled “INSTITUTIONS’ USE of DATA AND ANALYTICS for STUDENT SUCCESS”, Amelia Parnell (VP Research & Policy, NASPA), Darlena Jones (Dir. Assessment, Association for Insititutional Research), Alexis Wesaw (Dir. Data Analytics, NASPA), D. Christopher Brooks, (Dir. Research, EDUCAUSE), the top focal points of studies in Student Success include: success, affordability, enrollment management, efficiency and instructor performance.

The report highlights that, in support of these listed metrics, the primary use case for which institutions engage outside vendors is “Early Warning.” However, the vast majority of predictive and prescriptive analytics efforts are homegrown models and not API-enabled, scalable products. Those models aren’t being activated across the university today. And despite knowing that measurable definable campaigns are the best step forward this lack of “productizing” the insights for mass consumption holds back innovation and “Institution Readiness.”

Activating Student Success Nudge Campaigns

As institutions look to either deploy their homegrown models or become more “ready” they should look for institution-wide platforms. Student Affairs and Institutional Research professionals should be empowered to access student data that enables them to leverage their subject matter expertise to author Nudge Campaigns that target the metrics they seek. As McDonalds shows us, it isn’t just about having the data and insights from the homegrown analytics models, but being able to deploy, utilize and learn from them. Just like pairing fries with a shake on a hot, sunny day, marshaling all of those resources in order to improve student success is the best path towards continual improvement against a university’s student success metrics.

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