Three ways AI can boost engagement in digital learning

Artificial intelligence (AI) has never been bigger news. From the drama of Westworld on our TV screens (spoiler alert – the robots don’t like us much) to the front pages of our newspapers, AI is demonised and championed alike. Is Alexa cackling away as she plots how to overthrow her human overlords? Will the robots take our jobs? Or maybe, just maybe, could they help us?


Artificial or Augmented?

Those who see AI as a positive, like IBM, argue that it would be better viewed as ‘augmented intelligence’ - something that will enhance rather than surpass our own intelligence. AI can take the mundane aspects out of our jobs, leaving us free to take on more specialist tasks. These more difficult jobs will put increased emphasis on upskilling – but, thanks to AI, we’ll have more time to undertake training. What does this mean for digital learning? AI has the potential to transform L&D, and not just by increasing the need for training. While the elearning industry’s use of AI will always be less sophisticated than the likes of Siri, there are many ways we can embrace it to create a more personalised training experience. Learners of today expect this – and getting on board with this kind of AI will see your engagement levels skyrocket.

Here are the top three ways AI can improve engagement in your learning:

  1. Chatbots

    Whether we want support with fixing a problem or simply to find more information about a subject, we often find ourselves talking to chatbots. Gone are the frustrating days of pulling out an instruction manual and hunting through the index for something that may or may not help our issue. Instead, we want help with our exact question and we want it now. Luckily, our chatbot friends are on hand to provide this service. Using a chat-based interface and some clever coding in the background, Chatbots tailor their responses to our questions in a way that reflects human communication. In learning technologies, chatbots can provide invaluable support at the point of need. And we don’t even have to go full-on AI to achieve the same effects. For example, Kineo’s ‘chatbox’ functionality replicates the effect of a chatbot through a branching simulation. The chatbox will provide a tailored response to each of the learner’s queries, creating an active fact-finding experience - ‘artificial artificial intelligence’, if you will.

  2. Recommendation engines

    Recommendation engines have become part of everyday life, often without us even realising AI is pulling our strings. Who among us hasn’t stumbled across the perfect new product from Amazon’s ‘customers who bought this also bought…’ suggestions? Or found their new TV addiction via Netflix’s ‘top picks for you’? Personalisation is what keeps users returning – and it’s this use of algorithms and data that we can embrace to keep learners engaged.

    Tools like PredictionIO enable L&D to provide recommendations for learning activities based on what the learner’s peers have completed. By seeing what colleagues in similar positions have chosen to learn, users build a learning journey that is tailored to their role, industry and interests, rather than being taken on a pre-planned route through a course.

    Take a look at this case study to find out how Kineo and Vodafone used recommended learning to encourage users to take control of their training.

  3.  Content creation and curation

    AI won’t just help increase engagement when the learner is working through elearning – it can be used to boost engagement as early on as the content creation process. WildFire is an AI-driven tool that takes source content and transforms it into active learning content in just a few minutes. Alongside transforming documents, podcasts and videos into elearning, Wildfire also provides curated content, such as Wikipedia articles, TED talks and YouTube videos, to support the learning.

    Filtered is a similarly impactful tool. Its filtering algorithm curates content to create the most suitable learning path for the user. First, the Filter asks the learner a series of questions to find out what they need to know and their current proficiency level. After this quick analysis learners are presented with a fully personalised course, with subjects tailored to their exact needs.

The future is bright

AI dystopias will no doubt fill our screens for the foreseeable future, but we won’t let that scare us in the digital learning world. As AI increases in complexity we’ll find ever more creative ways to harness its power in engaging our learners. And who knows – maybe in years to come we’ll wonder how we ever got by without our robot friends to support us.

 
 
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