Everything we do online – from clicks to likes, from shares to the online purchases we make – is tracked, recorded and turned into big data. The new digital economy is based on this. We as users of the Internet are part of the huge data sets that come in an overwhelming volume, velocity and variety every second, and it is getting harder to escape it.

Our digital experiences are getting personalised

What we have in return is personalised digital experiences. To name a few examples: Facebook offers a completely personalised news feed experience. It runs an algorithm to estimate the relevancy of the content that is shown on your news feed. Instagram also relies on machine learning that creates a unique feed for everyone. You have a personalised feed based on certain factors like the interactions you have with other accounts and the time of the post. Spotify cheers you up with a “discover weekly” playlist curated for you every Monday. First, it creates a taste map to understand what genre you like by looking at your song history. Second, it goes to other users’ playlists that have the songs you listened to before and creates a playlist with the songs you have not played yet.

The recommendation systems of Amazon and Netflix do the same trick by recommending you the items and shows that you may like based on what you have purchased and seen before. According to a Netflix survey, an average Netflix user quits unless they come across something interesting within the first 60–90 seconds. And the list goes on. Personalisation seems to have become the punchline of all online services from shopping to music and it will no doubt continue to be so as customer satisfaction and addressing their personal needs are two essential growth strategies in business.

Personalisation in Digital Learning

When it comes to learning, digitalisation is becoming more and more widespread. An increasing number of educational institutions, companies and individuals are looking for digital solutions in education. According to Docebo’s latest e-learning report, the size of the e-learning market is expected to exceed USD 240 billion by 2023. Despite its increasing popularity, one of the biggest problems in e-learning though is still drop-out. People start online learning with a high level motivation but they tend to lose it through the end. Latest MOOC reports also painfully point out to low completion rates. A lot of academic studies show there might be numerous factors leading to this like learners’ attitude toward technology & e-learning, content quality, system quality or unmet expectations, which eventually cause drop-outs. Although the reasons for drop-out can be multiple or even completely personal regardless of e-learning, a big part of the solution can be personalisation of e-learning. What we usually see in e-learning environments is video lectures, multiple-choice quizzes and exams. It is mostly one-size-fits-all learning experience.

No doubt personalisation in education is not a new concept. In traditional education it is of high importance to address each student’s learning style and unique skills. Yet, it takes a lot of time, money and effort to make learning personalised for each learner in a traditional classroom.

Can technology play a role on making personalisation less effortless?

It already does. Advanced technologies like artificial intelligence now increase the prospects of creating personalised learning environments. We call these systems “adaptive”. It is the system’s ability to adapt to each learner’s unique needs that makes it adaptive. The intelligent systems track each learner’s activities and collect data about their learning behaviours. This allows for gaining useful insight into how they learn and interact with the course content and with other learners. What we have in return is the capacity to design learning paths that are suitable for each learner. Some examples are ClanedSmart Sparrow that developed smart learning platforms making it easy for educators to design more meaningful learning experiences for students. Dream Box offers different curriculum sequences, individualises the pace of learning and gives intelligent feedback by real-time data capture of learner’s behaviours online.

As the technology improves at this pace, we will have even more sophisticated learning systems in the future. We can imagine virtual learning assistants who would understand who we are, what we need to learn and how we learn. They would analyse our current cognitive, social and psychological states and generate a learning plan which is completely personalised and relevant. They would give us feedback at the right point and in the right time, guide and scaffold us when needed. They would even predict the most suitable times of a day in terms of learning performance and would constantly learn, re-learn and un-learn about us and engage us when our motivation drops. A futurist Robert Frey predicts that students will connect to virtual teachers from home by 2030. He even claims that students will learn 10 times faster than they do now.

What’s the bottomline for teachers?

World Economic Forum highlights that artificial intelligence is one of the biggest disruptors for all businesses and no doubt global tech companies like Google and education start-ups are adapting to the wind of technological transformation and build products to make learning more adaptive and personalised. Algorithms will get better at understanding humans, and educational products will get more sophisticated. What educators need to understand is the power of technology, how it can serve humans, and that it is not bad as long as we know what to do with it.

A true understanding of technology in the context of education requires rethinking the role of teachers. When learning meets personalisation through smart technologies, there will be less and less need for delivery of information by teachers. What learners will need the most is the human guidance and support towards achieving certain skills set such as creativity, communication, collaboration and critical thinking.