How learning analytics is nurturing educational insight and support

Feedback in education is two-way: Learners, through feedback, can revise and improve, but teachers benefit equally from getting feedback on learners’ progress. Learning analytics in educational technology makes it easy to identify and flag issues and provide learners with responsive, adaptive learning opportunities.

What is learning analytics?

Learning analytics refers to the use of data science to capture information about how learners use educational technology. Using learning analytics means collecting data to understand student performance so that educators can make informed, data-driven decisions.

Why has learning analytics becoming important in education?

Educators, like everyone else, are working in an increasingly digital landscape. Learners use digital platforms to acquire and share knowledge, and these present educators with opportunities to gain deep insights into how learners engage with materials. LA has multiple benefits:

  • It helps educators to identify common issues or flag poorly performing learners
  • It enables educators to pinpoint gaps in education that demand remedial assistance
  • It helps educators develop better, personalised student learning experiences including early-warning safety nets that increase student retention (the Learning Analytics Community Exchange lists these amongst other key benefits)
  • It helps eLearning course designers to improve  their courses with the help of data insights, so that future courses can meet learners’ needs better

How learning analytics is being used in EdTech to provide helpful adaptive learning

Many learners (especially in the African context) do not have access to quality after-hours, in-person educational support. Yet growing EdTech initiatives are providing learners with support via mobile devices and digital platforms.

Learners’ in-app actions are being used to predict learners’ foreseeable needs and suggest additional resources or tasks that supplement educational activities. This ‘intelligent design’ means that educational software developers are able to give learners products that adapt to their immediate educational needs.

The benefits of this adaptive use of learning analytics include:

  • Being able to supplement learners’ eLearning experiences and maximize educational support
  • Being able to guide learners’ digital activity without active teacher presence, making self-directed learning more productive

How is learning analytics being used?

Certain kinds of learner data collection has always been used to monitor progress (and reward achievement), such as the grading systems used around the world. Learning analytics today is used to track many more elements such as:

  • The time learners spend completing specific online tasks
  • How learners engage with educational content both in learning management systems and on social media

In 2011, education theorist George Siemens described how analytics empowers educators to make informed changes in education. Educators can understand better ‘how our inputs influence or produce outputs.’ There are several initiatives that are using learning analytics to do just this.

Learning analytics implementation in South Africa

Rob Paddock, the founder of the Cape Town-based eLearning service GetSmarter, describes learning analytics as central to GetSmarter’s teaching model. GetSmarter progressed from a canned approach to a model where learner data is reviewed in real-time to minimize the time lapse between learner input and corrective action.

Most crucially, learning analytics at GetSmarter were used to create a ‘safety net’: Learners who are at higher risk of failing are now contacted and given additional assistance early. This ensures that each learner has the best chance to stay on track and complete the learning platform’s courses.

Studies at The University of Pretoria and universities in the USA have also shown that using learning analytics to track and support underperforming learners and congratulate high achievers has been linked to improvements in overall learner retention.

Although learning analytics in the big data sense is still a relatively new area, prestigious higher learning institutions and socially aware EdTech start-ups alike are harnessing learning analytics successfully to improve learner experience and retention.

How to build on learning analytics gleaned from educational technology

Educational app development and publishing has grown in recent years. Gamified learning (using element of interactive game design in education) has increased. Because of this, educators have ways to gather learner data passively. Educational technology platforms help educators gain insights into individual learners’ strengths and problem areas. Here’s how to build on the valuable information learning analytics yield:

Gather insight into how to make educational content more engaging

Educational technology platforms such as video-based educational modules can measure and report how long each learner spends on a specific module or activity. This means that you can find out which modules learners abandon or skip over fastest and which keep learners glued.

These insights make it possible to learn from particularly engaging lessons and activities and apply their best facets to other interactive elements. It also opens up possibilities for testing which of different lesson formats gets the most learner engagement so you can develop educational content that is more valuable to learners.

Use learning analytics to measure and improve individual learner performance

Another benefit of learning analytics that comes with the embrace of educational technology is that educational platforms can be used to monitor and improve individual learner progress.

Assessment components such as quizzes or applied learning tasks can provide data on the topics that students tend to perform worst in, for example. This in turn can be used to increase lesson focus on key problem areas in a group context but can also be used to provide remedial intervention for learners individually.

The advantage of using learning analytics this way is that educators are notified early when leaners are struggling with lesson content. This makes it possible to intervene and arrange remedial processes before the learner has moved on to topics that build on shaky preceding understanding of content. Read more