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Universities have access to rich data sources that have many applications for learning analytics. One way that institutions can use learning analytics is to support student success and well-being on their learning journey.

“Learning analytics is understanding what data is telling you on the learning path of students,” said Mariana Robson, director of sales for EMEA at IntelliBoard, during a session at ɫ��ֱ�� Digital Universities MENA 2022. This process analyses a university’s data to indicate changes or interventions that could produce more positive outcomes for its students.

Data is assessed and presented to reflect the institution’s courses, students and learning activities. Given the demands from multiple departments and personnel, a dynamic system is needed to provide relevant information to coordinators, academics and students. Robson said coordinators, deans and faculties typically want big-picture data, while professors generally need information about individual students. The system needs to be able to serve both needs.

Learning analytics can help institutions identify students that are struggling. Robson said this is monitored in two ways. The first is rule-based, which uses parameters decided with the client to generate reports of students who need attention. Robson said that each client has different rules based on their goals, often based on student engagement. Some students might appear in a report if they haven’t interacted with their course for a certain amount of time or haven’t completed key activities. The flagged student can be sent personalised messages relevant to their situation and stage in the learning journey.

Machine learning is the second option for identifying at-risk students, which is based on historic learners’ data. Robson said clients are given the autonomy to train these models themselves or can leave it to IntelliBoard, which offers total backend control for systems.

Universities without a centralised data hub tend to struggle with siloed systems that don’t communicate with each other. As a result, time-consuming, manual analysis of data is the only option. “We have created a system which is a learning data hub,” Robson said. “We bring in all the data from different systems that initially do not communicate, and we put them in one place and allow our clients to get learning insights.”

Often institutions approach IntelliBoard with their end goals, such as improving retention or course engagement, but are unsure about the process required to meet these goals. “This is where we enter because we have the expertise,” Robson said. “Because we have been doing this for almost 10 years and have helped so many institutions already, we know how to get them there.”

By pooling its international experience, IntelliBoard has curated a portfolio of successful projects and uses that data to inform each new project. “All these countries are doing learning analytics and we learn from them, so it’s a very rich experience,” Robson said.

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