For Learning Institutions, the Future is Data
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For Learning Institutions, the Future is Data

Photo by:   Mario Gamboa
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By Mario Gamboa - Intelimetrica


It has grown increasingly common to pursue a bachelor's or a master's degree online.

This modality for accessing a formal education has gained traction in the US since the 1990s but, in Mexico, it has recently gathered speed for three reasons: cost, time, and the pandemic.

According to the MX Internet Association, an estimated 51 percent of students in Mexico turn to online education. The benefits they perceive are big savings in transportation costs, food expenses, and above all, in terms of the ​​time that can be spent on different leisure activities, such as family, traveling or developing a personal project.

In our country, important digital-native organizations, which offer a wide choice of quality, online higher education, have emerged. These institutions and their business models were originally designed as digital-first universities. Throughout the pandemic, these organizations did not need to adapt from an in-person learning model to fully remote; they were ready for it. However, these institutions do face many of the same challenges that their far more traditional counterparts struggle with. Specifically, developing and growing a team with deep technical expertise and promoting a data and analytics culture that allows them to scale out their business quickly across Latin America.

As an illustration, some of these organizations noticed a sharp surge in student enrollment during the pandemic but, after just a few months or even weeks, many students tended to leave their courses without completing them. What were the reasons for students dropping out? How does curriculum design or personal financial or psychological problems affect this behavior? How can these institutions react promptly to contain the student drop-out rate and push even more courses and learning programs to individuals already enrolled? These are fundamental questions for all learning institutions. Spoiler alert: data is the key.

Student attrition, at any point in time, will adversely impact institutions, digital or traditional, with the end result being misaligned financial planning, excess staffing (and increases in layoff compensations) or administrative costs, teacher reassignments and, most importantly, foregone revenue. In a word: inefficiency. What gives? Tracing events from different operating areas and gaining end-to-end visibility into the everyday complexities of a learning institution is a cornerstone and catalyzer to accelerate sound and timely decision-making regarding students at risk of attrition.

One such organization sought Intelimétrica’s advice to design and implement a comprehensive data lake, which allowed the university to unify a multiplicity of critical systems and eliminate information silos. In spite of the many disparate platforms (and some legacy systems) in place, our data engineers made sure every event and transaction within the organization was traceable, connected and, ultimately, visible to the university’s staff and leadership. In this way, the organization gained visibility into the performance of students, identified deviations from expected behaviors, and created workflows to ensure the execution of timely retention strategies.

In the future, this organization will also be able to design highly personalized learning programs by applying micro-segmentation and creating data-rich student profiles. Think of the thousands (or more) of possible curricula permutations designed to maximize student achievement and learning satisfaction. This will be achieved by leveraging data from when students first visit the university’s landing page, to the aggregation of detailed information from their social media profiles, to the understanding of their learning patterns and preferences captured in a Learning Management System, and so on.

Today, data lakes and analytics are empowering universities around the world, allowing them to understand, in near-real time, the critical events and patterns driving student behavior. What this promises into the future is learning institutions capable of correcting poor student performance before it’s too late, controlling student attrition risk by keeping them engaged and interested, and continuously enhancing and refining their acquisition strategies.

Photo by:   Mario Gamboa

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