Artificial Intelligence. Machine Learning. Words that are creating quite a stir everywhere, eh? Wondering what the fuss is all about? It wouldn’t be wrong to say that AI/ML and other emerging technologies are going to shape the future of e-learning, perhaps much of all learning.
Technology paradigms have shifted, and how! Flying cars and bikes may just become a reality, sooner than you think. Technological innovations have disrupted our lives like we never thought they would. There is one space where technology has created a tangible impact – in the e-learning industry.
As is with any new advancement, emerging technologies are often seen as a double-edged sword. The AI apocalypse that blockbuster movies like The Matrix series, i-Robot, and Avengers – Age of Ultron depict, show the worst-possible scenarios of AI gone all wrong. So, how exactly should you feel about this new development? Do you let it pass, or tighten your belts to embrace this change, lest you be left behind in the race of technology? Whatever be your choice, there is one truth that prevails.
As a learning & development (L&D) manager, you cannot ignore the impact that AI/ML has had on the learning space and how AI-powered advancements will change the way learners process and consume content.
For the uninitiated, Google’s definition of Artificial Intelligence says “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages”.
Let’s put into perspective Artificial Intelligence and Machine Learning in an organisation set up. If a computer gathers information about users learning behaviour, and updates over time, it would be the work of Machine Learning. If that same computer then categorized the learning behaviour based on that information collected, it’s an AI system that the computers used to achieve that task. More simply put, Machine Learning is a part of AI. AI is used to categorize learner behaviour based on the refined information that ML gathers.
We all know that learning happens differently for different people. What one person takes a day to learn can possibly take a week for another to grasp. This poses a huge challenge for course creators to maintain the balance between different learner capacities so that the learning is effective. With technologies like Artificial Intelligence, it is possible to create customized lessons that allow for individualized pace, different content and learning styles. This makes learning more efficient and engaging.
AI-powered chatbots can improve the learners’ eLearning experience by providing personalized learning paths, and delivering instant clarifications and feedback.
Recommendation engines can make suggestions based on the learners’ past actions. They look for patterns and predict how likely a learner is to be part of a group, and then making recommendations accordingly.
Personalisation can deliver the actual learning experience depending on learners’ past interaction and performance, and based on their level of experience in the field.
Insight generation tools can measure not only the time a learner spends on a course, but also the impact of learning on the learner’s performance.
Moving from discussion to implementation, we found a few compelling case studies of e-learning powered by AI/ML on the ground.
Embibe is a startup focussed on providing personalised learning experiences to students with the help of Artifical Intelligence. As part of their solutions, they do an extensive study of the impact of student behaviour on learning outcomes. Based on the observations, they propose ways to improve student behaviour and learning outcomes. All through their AI platform.
Woodside Energy, an Australian independent oil and gas company, turned to IBM Watson to collate and make 30 years of practical engineering experience easily available to all employees of the organisation. IBM Watson was able to collate all the available information, and provide instant responses to users whenever they posed any question. Over 80% of employees at Woodside Energy were seen adopting Watson for their day-to-day work. The impact of the AI-powered Watson? According to IBM, “Watson helped reduce the time spent searching for expert knowledge by 75%.” That’s a lot of time on hand, isn’t it?
These are but a few implementations that the e-learning industry has seen. The question, really, is whether the world of learning has indeed been swept away by the AI storm? Have organisations world over matured to face this challenge head-on?
Personally, I believe, it’s a NO.
Yes, the emergence of these technologies is real. Their advantages are something that cannot be ignored. Yet, we have quite a distance to cover to embrace and adapt to the large-scale scope of AI and other technologies in the e-learning space.
Personal beliefs aside, it is undeniable that the scope of Artificial Intelligence is huge. As marketers and L&D professionals, it is but wise to be open to change. Make the shift soon enough to remain in the race of survival.
AI-driven e-learning is still nascent, giving L&D managers the time and space to prepare for the future. The most practical way forward for companies is to start a POC or pilot in one targeted area and equip themselves with the knowledge for future large-scale deployments in the area. Small steps to include emerging tech in your e-learning strategy and implementation will help lay the groundwork to transform learners’ experience in the years to come.
In the end, what will win will be learner-centricity: whether AI-powered, or powered by the good old chalk and duster, learning outcomes that make a difference in skill building will be the winner in the marketplace.
Do get in touch with us to explore implementing these technologies as part of your org’s e-learning strategy. Happy learning.