Data analytics are increasingly vital for streamlining campus operations and driving strategy to improve the student experience. AI has spawned a web of technologies and practices that should lead to more advancements, according to a new report from EDUCAUSE, an education technology nonprofit.
“The future of institutional effectiveness, student success and innovation will hinge on how well colleges and universities adapt their data strategies to this changing environment,” the report read.
International higher ed and technology leaders cited in the report have identified six trends with the greatest potential to transform data analytics.
‘Mixed methods’ research
‘Mixed methods’ research allows researchers to more clearly analyze qualitative data at scale and create a more comprehensive picture of student feedback. While quantitative data are traditionally easier to assess, researchers who fail to analyze the “why” and “how” lose the nuance found in open-ended, text-based answers, the report asserts.
Auburn University uses the mixed methods to gain more insightful feedback from online students.
Scale data literacy across the institution
Institutions that fail to provide adequate data literacy training to staff could widen the second digital divide and reinforce silos in the process. One-off training programs will quickly become outdated as technology continues evolve.
Louisiana State University is building data literacy through its Presidential Data Analytics Fellowship, which invites mid-level administrators to workshops, mentoring and hands-on projects that factor data into decision-making.
‘Data mesh architecture’
‘Mesh architecture’ flips the script on how large institutions store information by decentralizing data that is typically managed by a central IT team.
When different business units own and distribute data to the rest of the university, it reduces bottlenecks and encourages cross-department collaboration.
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Mesh architecture can enhance data literacy and analytics by expanding access to a broader range of stakeholders. However, leaders should offload data slowly before overhauling campus systems, the report recommends.
‘Federated data governance’
‘Federated data governance’ uses a central governing body to enforce compliance and standards while allowing separate departments to manage their own data based on the guidelines. This model goes hand-in-hand with the data mesh architecture previously discussed.
Federated governance allowed Canada’s McMaster University to set data quality and consistency rules while letting HR, student services and finance units control their own information. Embedding governance into daily operations supports better decision-making and builds trust in campus data.
AI-powered decision intelligence
Strategies that give decision-makers better intelligence are moving beyond the analysis of past events. AI streamlines tedious work, freeing leaders to examine nuances and predict future outcomes.
The report advised data-empowered leaders to invest in resources that monitor AI output and prioritize transparency.
AI assistants
Faculty and staff can benefit from an AI-powered assistant or chatbot that quickly accesses data, codes reports and generates data visualizations.
Montclair State University embedded an AI agent within its enrollment marketing dashboard to help staff deliver personalized advertisements to prospective students.
Leaders must be wary of chatbot hallucinations and of providing AI with sensitive information that could be accessed by unauthorized users. Administrators must probe for weaknesses of AI assistants to build guardrails.
