Below is a broad category of commonly used AI tools and techniques being applied in the L&D space. There are some overlaps of functions and features between categories. For examples, some chatbots also offer an adaptive learning experience by suggesting personalized next steps within the chatbot responses; adaptive learning platforms typically analyze learners’ responses, recommend learning paths and content as well as offer some kind of learning analytics and to some extent learning predictions.
Chatbots / Conversational Agents
Chatbots are software applications that mimic written or spoken human speech for the purposes of simulating a conversation with a real person. It is commonly used for customer support and general communication with customers in businesses and can also be used in learning applications.
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Adaptive Learning Experience Platforms
Previously known as Intelligent Tutoring Systems (ITS), they have evolved into adaptive learning platforms with pathways that updates dynamically as learners gain competencies/knowledge. Some adaptive learning experience platforms also monitor learners’ progress (their successes, misconceptions, misses) and provide personalized step-by-step instructions.
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Content Creation and Management
AI-enabled content creation allows content to be generated at scale.
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Predictive Analytics / Learning Analytics
A relatively new yet growing field, learning analytics is the measurement, collection, analysis, and reporting of data about learners, learning experiences, and learning programs for the purpose of understanding and optimizing learning and its impact on an organization’s performance.
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Auto Grading and Assessments
Automatic grading of written essays with the ability for the robo-graders to sort and “learn” what good essays look like and be able to assign grades accordingly. Some of the systems claim to have the ability to improve over time based on the massive amount of data input.
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Augmented and Virtual Reality
Augmented Reality (AR) and Virtual Reality (VR) are two technologies that are maturing rapidly for training and learning purpose. AR overlays digital elements to a real-world view often by using the camera on a smartphone while VR provides a complete immersion experience that shuts out the physical world. AR and VR both make use of AI techniques such as natural language processing, image recognition, and selective rendering.
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