How advanced analytics is shaping the future of edtech

We have all probably heard by now that “data is the new oil” and while there might be a smidge of hyperbole in that statement, it is safe to say that we have never had access to the amount of data as we do now. While an abundance of data exists across all major industries, extracting the right insights from it to shape better customer experiences remains aspirational for most.

The world of education is no different and in a rapidly evolving ecosystem that is characterized by virtual or blended learning models, analytics can play a significant role in improving decision making and learning effectiveness across the value chain.

 It is important to point out that although students would be one of the major beneficiaries of advanced learning analytics, its application can prove to be equally effective across various other functions like admissions, marketing, course development, recruitment and alumni relations. However, let us start at the heart of the matter and understand how analytics can be a pivotal driver of educational reforms by empowering teachers to use accurate data to improve student performance.

Generating improved learning outcomes

As learning becomes increasingly virtual, it is not just the richness of content but also its delivery and application that go a long way in determining whether learners are able to grasp and retain complex concepts. It is now more important than ever for instructors to use reinforcement or assurance mechanisms to validate that their cohorts are on the right path towards achieving the desired learning outcomes. 

Learning analytics is just what the doctor ordered as it is now possible to capture critical learning events like the amount of time a learner spent on a page, assessments attempted, consumption of video or audio content and the quality of assignments turned in. While an ocean of such data can be captured with ease, it is important to leverage a learning analytics platform that can receive and process such data to provide intelligent insights at scale. 

The hyper competitive environment we all find ourselves in requires us to accentuate our strengths and extract the most out of our abilities. For instance, in the world of competitive exams, a fine line distinguishes the great from the very good and often it boils down to finding that extra minute or two which can make all the difference. Advanced analytics can be applied during mock tests to determine areas of improvement or to chart out the order in which questions are to be attempted to achieve the best results. 

The role of AI in developing and curating content 

There has been an uptick of AI (artificial intelligence) in curating content as NLP (natural language processing) based algorithms help in automatically aligning learning content that is delivered in the form of engaging bite sized capsules over mobile devices. This along with conversational edtech and social P2P (peer-to-peer) learning has resulted in creating Spotify like content that is experiential, informal, and highly shareable.   

Analytics outside the classroom -- course development, enrollment, retention and growth 

Let us now take a step outside the classroom and understand how the insights captured about learner behavior can help in course development that is closely aligned to the specific needs of learners. The boundless information captured from a learning analytics platform can be used to generate rich metadata that helps in determining the type of content best aligned to a curriculum and identifying the optimal mode of delivery. The magic really happens when the content profile is matched with the learner profile as the adaptive nature of a learning platform enables learners to choose the content best suited to their needs and attain the required proficiency. 

The administrative side of the education world can also experience tremendous upside with the use of advanced analytics. Admissions and enrollment officers can use insights provided from analytics to build an ideal target persona by collating varied types of demographic information. Marketing efforts can then be aligned to focus on these specific clusters that have the highest probability of converting into subscribers or students.   

In a world that is inundated with distractions, analytics are key to ensuring high levels of student engagement and pointing out red flags about diminishing interest before it becomes irreversible. Analytics have directly helped in improving the impact of student support systems as such teams now have access to better and more timely insights. Hence, it is now much easier to heed the wisdom of prevention being better than cure to identify and coach at risk students who otherwise might have eventually dropped out.  

In addition, diving deep into available data and utilizing analytics can also help placement officers, academic planners, course developers and even alumni relations teams to make more informed and timely decisions that are connected to patterns that might just be invisible to the naked eye. 

I believe we are at an inflection point in the way education is conceptualized, created, and consumed. The advent of digital technologies and the convergence of AI, immersive learning and blockchain will further empower learners, instructors, and facilitators to chart a bold new future of edtech that makes learning increasingly immersive, tactile, and memorable.