How Machine Learning Will Shape the Future of E- Learning

Education Technology Insights | Thursday, January 24, 2019

Technology and education have crossed paths for the benefit and improvement of society. Advancements like e-learning and online education have become the standards of academic instruction today. Machine Learning (ML) algorithms are used to contribute to these better learning outcomes. The advent of ML techniques has helped in the evolution of platforms and tools that support e-learning flourish.

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Applications of Machine Learning

1. Personalized learning paths: A learning path allows learners to build their knowledge progressively through learning materials or sequence of courses. Personalized learning paths emphasize learner specific goals and preferences. This model uses practical tools to help students to increase motivation and commitment to learning. The idea is easy to implement when one teacher engages the same group of students throughout an academic year. Self-assessment is a key factor associated with personalized learning path.

2. Chatbots: They provide conversational answers and serve as quick reference guides. Bots also reinforce the learning experience by imparting relevant information when needed. They deliver data-oriented results to help learners save time and resources.

3. Performance indicator: Pinpointing certain learning patterns is enabled with performance indicators, for example, significant spikes in course failing. ML provides a more effective way to analyze learner engagement data and identify patterns for content redesigning.

The automatic evaluation process is an advantage of machine learning. This will be an opportunity for completely unbiased grading that cannot be influenced by any external factors. It gives a more realistic view of student's progress and achievements.

ML can also help educators to look forward to the future. They can solve the academic issues with the data in their system. It can also indicate students at the risk of dropping out or receiving greater disciplinary actions. ML presents advantageous features for students and teachers. It can be quite expensive to purchase all equipment and programs to make e-learning an effective solution for learners.

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