From customized learning to creating AI based content, and from language translations at scale to AI generated virtual presenters—the adoption of AI will increase over time. In this article, we’ll explore what’s in store for AI-centric eLearning.
Evolution of AI in eLearning
While not yet fully mainstream, over the past few years, Artificial Intelligence (AI) has made significant strides in the realm of eLearning. Content and visuals are two crucial aspects of eLearning where AI-based tools have begun playing an increasing role. The use of sophisticated algorithms, by companies like Microsoft and its partner, OpenAI, to simulate human-like intelligence has produced Generative Pre-trained Transformer (GPT) technology, also known as ChatGPT, as well as DALL.E, a tool to produce AI-generated graphics and images. Google’s Bard is yet another AI tool being leveraged in eLearning.
These AI-based tools will significantly change how eLearning content is produced. While ChatGPT and Bard can be useful for generating descriptive (text-based) eLearning, DALL.E has shown promise in image-based eLearning applications. eLearning creators are also beginning to use other AI-based tools, such as Jasper, CopySmith, and ShortlyAI, for short-form content generation, and Frase for long-form content creation. Furthermore, natural language processing (NLP) algorithms (e.g., Chatbots) are gradually being used for first-line eLearning support, in employee onboarding applications, with performance support tools, and for voice-activated learning support.
What are the Benefits of AI in eLearning?
AI-based tools have tremendous potential in eLearning. From creating and optimizing content to personalizing lesson plans and helping with assessment and evaluation, L&D teams can use these tools effectively. Some other benefits include:
- Using NLP to optimize content creation. AI algorithms can optimize content to meet learner performance metrics and preference criteria.
- Faster content creation. Because AI is automated and more accurate than humans, it results in producing content faster.
- Better learning delivery. By supporting educators with better assessments, highlighting learning preferences and knowledge gaps, and using immersive, intelligent tutoring, AI in eLearning can help deliver eLearning more effectively.
- Better learner engagement. With AI-enabled virtual tutors and Chatbots, learners receive instant, personalized support and feedback. This enhances learner motivation and engagement. The ability to produce more immersive content (graphics, videos) leads to better learner engagement.
- Better insights. Algorithmic learning data processing, including statistics on learner preferences, test score evaluation, and participation and engagement levels, gives training staff better insight into eLearning effectiveness.
- Ability to create personalized learning. AI can automatically create customized flashcards, quizzes, lesson summaries, and other personalized learning materials.
- 24×7 Virtual learner assistance and support. AI tools embedded in eLearning, like Chatbots and Virtual Assistants, support and guide learners with interventions such as Learning-on-the-go, Just-in-time-learning, Learning at the time/place of need, and performance support applications.
Current State of the Use of AI in eLearning
eLearning is entrenched as a learning strategy across all industries, especially now, as hybrid work has attained prominence. With global demand for online learning soaring, AI has emerged as a useful ally for L&D teams who are stretched for time and resources. The speed at which AI-based tools can produce learning content, for eLearning design and development teams to then refine and finalize, is unparalleled. And many learning-focused organizations are leveraging that ability.
The use of AI in eLearning is also widely practiced for personalizing learning content to fit the needs of individual learners and delivering effective eLearning experiences. AI algorithms take copious amounts of data from learning and content management systems and use it to optimize learning delivery.
How Will AI Transform eLearning Content Development?
AI will force a paradigm shift in how eLearning content is developed. Some aspects of that transformation will come from:
- AI-assisted content development: Intelligent tools used for AI in eLearning will help develop a wider array of eLearning content.
- AI-generated virtual presenters: Chatbots and personal learning assistants will fill in as virtual presenters and virtual tutors.
- AI for generating assessments and quizzes: AI-generated quizzes and assessments will personalize learning tests, quizzes, and evaluations.
- Leveraging AI to make learning more accessible: In league with Assistive Technologies (AT), AI will make eLearning more accessible to learners with disabilities.
- AI for translation and localization: Thanks to AI-powered tools, eLearning courses will now lend themselves to (almost) instantaneous localization and translation.
- AI-powered interactive content: AI tools will make it easier to produce highly interactive and immersive eLearning content, such as short games and simulations.
- AI-generated images and videos: AI-powered videos, digitization, and graphic-generation tools will create more relevant videos and imagery to supplement course content.
- Leveraging AI to automate repeated content development tasks: Generative AI will learn to take over repeatable and mundane development tasks, creating space for developers to focus on better course design and delivery.
How Will AI Transform Learning Delivery?
Implementing AI in eLearning will revolutionize online learning beyond just content development. Adaptive learning tools will personalize learning by adapting and customizing courses to fit learner needs. L&D teams will use AI to make eLearning strategies such as mLearning, Microlearning, and Gamification more immersive and effective.
The use of Virtual Assistants and Chatbots will make learning more “available” (24×7) and save valuable trainer time. AI algorithms will make self-assessments, evaluations, and progress tracking more accurate and meaningful.
By “watching, listening, and learning” how people learn, AI tools will tap into the vast amounts of data generated by LMS and LXP systems to mine for learning opportunities. Powerful AI-based data analytic engines will offer new insights when assessing and reporting on learning interactions like learning preferences, gaps, and weak areas.
To understand the transformative nature of these technologies, in the context of creating eLearning, consider this use case: Course designers use ChatGPT to produce descriptive content for storyboarding and supplement it with powerful storyboarding visuals using DALL.E. The development team then uses the AI-generated storyboard as input into rapid course authoring tools such as Adobe Suite or Articulate Storyline Rise. The result: Powerful, impactful, realistic eLearning courses – created in record time!
What Does the Future Hold for AI in eLearning?
As the use of AI in eLearning evolves, it’ll become more entrenched in it. More rapid AI-assisted content generation, better eLearning personalization, and use of highly immersive content (simulations, use cases, case studies, VR/AR/XR, and game-based learning) – are all in the cards.
As AI-based eLearning tools become more mainstream, they’ll help in identifying at-risk learners, so trainers can implement timely interventions to help them. Trainers will also get support in improving the learning process through AI-enabled technologies that assess learner stress, attention spans, distractions, and disengagement.
“One-click”, fully SCORM-compliant eLearning generation capabilities are not a long way off. We see future developments in AI-supported technologies such as Machine Learning, Deep Learning, and Reinforcement Learning, integrated to support L&D.
Pitfalls to Avoid While Leveraging AI in eLearning
The use of AI in eLearning requires careful thought and attention. Left unchecked, AI can stifle independent thinking in content creation and may even lead to plagiarism and copyright infringements. Other moral concerns include the algorithmic creation of misleading and fake content and the extent of collecting and analyzing learners’ personal and private data.
Conclusion
AI-driven content creation can revolutionize how eLearning courses are created. From customizing learning pathways for individual learners to creating AI based content, we expect the adoption of AI to increase as the year progresses. Some near-term use cases of AI in content production include language translations at scale, AI generated virtual presenters, and AI generated videos. AI-generated content will also enable you to drive personalization and course customization at a scale. Nevertheless, it is also critical to have the necessary human intervention at the right juncture on the development process of AI generated content to ensure learning is human-centered and provides value to the learner and the business.
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