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AI in eLearning Systems

Although a part of many eLearning platforms in some form or the other for a long time, artificial intelligence still spurs considerable excitement about the future of how we teach and learn, especially in eLearning, the present and future of education. It’s about designing intelligent software that can analyze its environment and users to make intelligent choices for online learning. 

Learners process content in different ways and at varying speeds. Preferences of one may not be suitable for others. While traditional methods of teaching do not address such concerns, AI-powered eLearning makes it a reality, that of creating customized learning paces and tailoring content as per need. E-learning equipped with intelligence helps recognize and assess students’ understanding of a concept without manual intervention, and then suggest the next steps for improvement.

We can find existing applications of AI in several areas of eLearning. A common example could be a quiz program that springs the next set of questions to ask a learner based on his/her previous responses in order to strengthen his weak areas. e.g., focusing on topics where user repeatedly defaults or skipping to a higher level in case of proficiency.

Artificial intelligence also acts as a virtual tutor/mentor and answer questions in real-time by addressing points of confusion as soon as they arise. It helps create an interactive environment for each student which increases the engagement level, thereby improving course completion rates.

Introspectively, AI has helped us to fundamentally reimagine the role of an educator in the eLearning system. Today, AI impacts the modern educational system in the areas of adaptive learning, virtual teachers and lecturers, customized digital learning interfaces, automated grading, automated plagiarism checking and so much more.

Many applications of AI in eLearning include concepts like deep-learning systems that can translate lectures in one language to another for a student’s understanding. Similar technologies in voice recognition and text summarization can transcribe entire lectures with striking precision. Machine learning algorithms can also flag areas of bias, complexity, and ambiguity for closer review by the instructor. 

Several companies across the world have already forayed deep into the technology such as Duolingo, a popular language learning app that utilizes machine learning and natural language processing in numerous ways -predicting learners’ word strength, identifying the right sentences to help learners make progress and recommending immersion practice documents (translations) based on the learner’s progress. When dealing with millions of users, AI helps learning apps like Duolingo to comfortably adapt as per individual user.

E-Learning and AI are emerging as a clear winner, yet a lot is still to be explored. With AI-backed eLearning, instead of pre-defined roadmaps, the learner takes more control over the direction of their learning, leading to better outcomes for all participants.

  • Posted Date: 04-MAR-2020