The last year has seen online learning increase prolifically. Virtual schooling has led much of this transformation as teachers the world over have tried to engage students over video and using online education platforms. One often overlooked dimension of the online learning revolution is the transformation of professional development. In order to move innovation forward, we must invest in the on-going education of our current and future business leaders.
Yet, a skills divide is not only emerging, it’s growing. In the UK, 48% of businesses are recruiting for roles that require hard data skills. Yet almost half (46%) have struggled to find talent over the last two years. While many companies will strive to train their own workers, there is still a lack of confidence in their ability to do so. This shortage of skills and expertise is concerning to leadership, manageers, and employees alike. To aid in the future of learning, let’s explore three types of artificial intelligence (AI) that may help.
Automation of Predictable, Routine Tasks
Automation of routine tasks has been emerging in online learning platforms for many years. Apps like Duolingo offer lessons and assessments that personalize learning by modeling student outcomes. The app provides endless practice exercises to help participants learn a foreign language, which is also used to inform the algorithms that drive the next set of exercises the learner sees.
Duolingo uses every bit of data collected about each learner to model what they know and how the app can best help them learn down to the individual word. There are nearly limitless ways for the app to inexhaustibly offer new learning elements such as vocabulary, grammar exercises, and other language lessons. This approach is not limited to the study of languages. It is also being applied to subjects such as math, science, and coding. Whatever the subject, automated systems can be used to relieve instructors from having to develop routine exercises and grade assignments. While this type of automation has been part of online learning for a while, AI methods and the broad availability of learner data has enabled them to become more sophisticated and they can now offer students truly personalized experiences.
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Generating Novel Insights Through Data
Massive collections of data are generated when learners interact with learning systems. This is increasingly being used to understand how students learn and provide real-time feedback to improve the learning experience and drive better outcomes. Previously, learner data was almost considered a burden to schools and administrators; now, it is being used to create new business value for educational institutions while delivering meaningful insights to the learner. The sheer volume of data presents opportunities — such data can be used to model how students interact with content, instructors, and peers.
In colleges and universities, for example, student retention is a huge issue. Schools are increasingly using their new sources of data and predictive analytics to optimize performance and target students who might need more support. Generating novel insights through data is another way AI is used in educational settings that will be increasingly beneficial in the future.
Helping Students Connect
Perhaps the most interesting way that AI is being used to enhance learning involves helping people become part of online learning communities. This emergent area of development has enormous potential to change the landscape of learning. When we move from physical to online learning experiences, we often lose the social element of an educational environment — whether we’re talking about K12 or business schools.
All learning is social. So, what happens when you take away peers and peer interaction? Having people do everything individually means that learners never benefit from new and novel ways of thinking. Even with mostly in-person learning, online communities can be used to enhance and extend peer-to-peer interactions. Human-centered AIs can be used to put students into affinity groups, provide feedback about peer interactions, foster collaboration, and create new connections.
With these types of data, we can learn how people connect and communicate, model these interactions, and provide students with information about each other and themselves.
In summary, automation, predictive analytics, and human-centered AIs are being used to enhance online learning experiences. Education communities must seize these new technologies in order to develop a digitally skilled workforce — now and in the future.
Written by Beth Porter, President, COO & Co-founder, Esme Learning