Case Study

Case Study

University of Brighton

Posted by Admin on January 12, 2019

The University of Brighton, based in the UK, recently worked with Tribal on an exciting pilot project using Tribal Edge Student Insight, new predictive analytics software. The university were introduced to the software through the Jisc Effective Learning Analytics pathfinder scheme, and the project had ground-breaking results. 

Getting the right data 

The University of Brighton were already Tribal customers, using the SITS: Vision Student Information System to manage their student records and Tribal’s Student Information Desk. Data from both Tribal systems were used in the project, alongside data from Brighton’s Blackboard learning environment. The Student Insight software would take 3 years of student data from the university and make predictions based on the data of the students most at risk. The software would also crucially help identify the factors that most indicated student success – extremely valuable information for the university.

Katie Piatt, the eLearning Services Manager at the University of Brighton was heavily involved with the pilot project, and worked closely with Richard Palmer, Product Manager at Tribal. Katie said:

“The Jisc scheme allowed the University of Brighton to get excited about data analytics, and our partnership with Tribal was the perfect fit. The Tribal Team helped us in the process of transferring 3 years’ worth of data and the Student Insight technology integrated this seamlessly. The analytics gained from using the product were not based on assumptions, they were based on real data and patterns emerging from the data.”

Discovering actionable insights 

From the data analysed, the university could decide what actions to take, identify specific student issues and start to plan steps to intervene. The data analysis was an extremely collaborative process, Tribal held regular user groups and the University of Brighton were part of the development of the product.

The university identified through the project that they needed to improve their data consistencies and internal processes, so they had effective procedures in place to intervene when students were known to be at risk.  

Katie continued: 

“A key phrase in a learning analytics project is actionable insights. It is amazing what you can do with machine learning, but if it tells us information that doesn’t enable us to make a change there is no point in the exercise.  From Student Insight, we have been able to identify students at risk of dropping out or achieving below their capabilities and create steps to intervene.” 

Student Insight allowed the University of Brighton is see patterns and trends in their data they hadn’t even considered, the product identified these without any assumptions or errors in judgment, which could occur from internal data analysis teams.

Katie concluded:

“It is a scary world for our teams to get their head around the fact I’m not just guessing that a student is at risk, or guessing that age on entry is important, we have got 3 years’ worth of data evidence that is pointing exactly to that…One of the things we found fascinating from Student Insight were the identification of factors that influenced retention, because the results were not what we expected. We identified that age on entry was a massive factor regarding whether students went on to succeed. This helped us to realise that we focus on the 18-year-old entering university, but are we missing a trick? Is there something going on with the 21-25-year olds, that means we are not offering them the best support possible?”

The University of Brighton used Student Insight for around year, the university has a strategic plan in place for the next five years, and learning analytics is embedded in that. For the university, it’s about being able to support their students through the intelligent use of data and using Student Insight has helped shape their thinking in the learning analytics area. 

Working with Tribal

Katie Piatt, the eLearning Services Manager at the University of Brighton said:

“It was a good experience and I enjoyed working with Richard Palmer and the Tribal team, the user groups were valuable, it was really a great project to be involved with. Richard really helped us in the development of the product, shaping it to our needs and advising on what we could achieve in the future. Richard had a really clear vision of how our data could be best used to help students succeed. Craig Petch from Tribal did all our system integrations for us, so he knows the inside of our database better than most people at the university!”

Looking to the Future 

This explorative pilot project allowed the University of Brighton to get excited about data analytics, through a partnership with Tribal that was an excellent fit with their current systems and processes. Tribal Edge Student Insight was a useful product to allow the university to explore learning analytics, understand what it can do for them and learn about what processes and data consistencies they need before making an investment in a system. They are now at a stage where they are reassessing their data and internal processes and interventions, with a view to reengage in the future, when they are better placed to do so.

To conclude, Katie said: 

“I would recommend Tribal’s Student Insight tool because of it’s power to identify patterns and factors from years’ worth of data. However good your in-house data analysis team is, they are going to be looking for correlations between data. Your team can’t compare all the data you have seamlessly, whereas with Student Insight you can. It is really examining all the data you have and pulling up themes, patterns and relationships that you couldn’t guess. It’s an incredibly powerful way of understanding your data in new ways.”

University of Brighton experienced these main benefits from using Student Insight:  

  • They uncovered the key factors that influence retention rates. 
  • They uncovered the key factors that influence student success. 
  • The results of the project made them rethink their assumptions e.g. they assumed disability, or lower entry qualifications would be most important, however these were not discovered to be the factors influencing success and retention rates based on their data. 
  • They recognised the need for a learning analytics steering group to get the next steps in place for interventions in their university. 
  • They experienced an easy integration between data systems that feed into the Student Insight tool. 
  • Through Student Insight, they uncovered patterns and factors from years of data quickly and accurately, which would not have been possible with an in-house data analysis team. 

Discover more about Tribal Edge Student Insight

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