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Learn Your Way: How we use learner analytics to improve online learning

We talk to Andy Ramsden, ULaw’s Director of Technology Enhanced Learning & Teaching and Learning Analytics about how analytics are improving the way we teach and learn online.

Just over a year into his appointment Andy Ramsden, ULaw’s Director of Technology Enhanced Learning & Teaching and Learning Analytics reflects on some of the impressive analytics work undertaken by his team: “In terms of where we sit alongside other institutions, ULaw is at the forefront of using learner-led data to create tools for learning.”

“We started by creating pilot schemes for the LLB and SQE,” he said. “We had a differing focus for each cohort. For the SQE we looked at specific challenges faced by that group, and for an undergraduate LLB pilot in Birmingham, we looked at a broader spectrum of information using a system called Stream.”

While the technology behind gathering Learner analytics/data may be alien to some, the logic behind studying students’ progress and behaviours to improve performance is clear. But what does this look like for students studying with us on and offline?  One way in which students will benefit from these developments is by receiving visualisations of their current progress and potentially their predicted progress. These user-friendly graphics will become a familiar addition to the student dashboard and will be automated from the data of weekly tests and tracking. By tracking, we mean assessing the frequency with which learners enter their learning portals and visit different virtual areas, such as resources or emails. During the Birmingham pilot, complete algorithms were generated by learners as they undertook their regular assessments and explored online space.

Tutors have begun using these graphics as go-to points of reference when reviewing individuals’ development. They also offer the opportunity to track an entire cohort’s progress in comparison to their counterparts in different campuses/year-groups. It’s important to understand that all the detailed information stored about students’ learning behaviours will be kept and used securely in-line with global GDPR and will trigger positive messaging to students, whether it be via email or social tools. “These tools are there to empower students through understandable visualisation, in terms of seeing their own engagement over time,” said Andy.

How does interface-based technology like this relate to something as communication-based debating and mooting? In phase two of the Learner Analytics development, Andy, and his growing team, will start creating unique Learner profiles for each student. These will trace competency results in more interpersonal skills-based activities, allowing a constant picture of how an individual is developing skills and confidence in these highly performance-based areas.

After acting as a lead analytics consultant for Blackboard and helping gather intelligence on learners in Africa and Middle East, Andy is enthused with how much ULaw’s existing learning and teaching model is already equipped to embrace learner analytics. "ULaw is unusual and great, in that it offers a standardised learning and teaching model – which already collects data. Giving learners and tutors greater awareness of what they are doing well is front and centre in this innovative piece of work.”


If you would like to learn online with ULaw and experience the support we offer first-hand, find out more here.