AI-based Adaptive Learning

Artificial Intelligence is a fascinating topic with applications in almost every field. One of such applications is the field of learning. Nowadays, people are trying to focus more on utilising the learning techniques that help solve their doubts and keep them updated with the newest advancements in their field. Adaptive learning is one such technique which focuses on an individual's strengths and weaknesses and modifies itself according to an individual's behaviour as well as needs. However, adaptive learning is difficult to implement when there is a large number of people. With the help of AI, this task can be made easier so that the quality of learning can be improved. The issue of the number of learners is resolved with the help of AI, as there is no limit to that. AI algorithms understand the behaviour of each learner and based on that various suggestions are made to enhance the knowledge of the learner as well as solve his/her doubts. For example, what happens in traditional learning techniques is that it becomes difficult for the professor to analyze each student's performance, solve the doubts as well as teach each student individually according to his/her grasping power, mental abilities and field of interest.

Now, suppose we have implemented an AI-based adaptive learning technique in classrooms. The professor can take online classes where there are no restrictions on the number of students and each student's performance will be analyzed by the AI bots. If a student makes the same mistakes more than once, he/she will be provided with assignments of similar queries by the program and materials on that topic with better explanations will be shared to help the student refine. Eventually, this will help the student understand the subject better.

The best part is that this technique can be used by anyone who is willing to learn and enhance one's knowledge in various areas. This technique can be implemented in areas like economy, science, language, technology, etc.

Workflow of an AI-based Adaptive Learning Technique:

1. Proper assessment of learner's knowledge
2. Providing content based on performance analysis of learner
3. Interaction with real-time feedback data

The benefits of the AI-based Adaptive Learning technique:

1. Minimizes budget by saving training resources
2. Requires little human intervention
3. For tracking training efficiency and learners' performance, performs deep analytics
4. Saves time to train
5. Focuses on the quality of learning of each learner individually

Applications that use the AI-based Adaptive Learning:

• Duolingo
• Prodigy Math
• Embibe
• Lexia PowerUp

It supports one-to-one interaction between the learner and the teacher. There are people who cannot ask questions in public or are afraid of public speaking. This technique helps boost the learner's confidence and motivates him/her to ask more queries. However, this is a negative aspect of one-to-one interaction since it forces people to be more introverted and doesn't help in improving their skills in public speaking. There are a few more limitations associated with this technique such as more training time, unpredictable digital experiences, difficulty in implementing AI models, etc.

However, looking from a broader perspective, the AI-based Adaptive Learning technique is proved to be one of the best learning techniques having the ability to provide quality education, better doubt solving abilities, one-to-one interactions, orientation toward individual interests and self-modification quality.

Thank you,

Khushi Naik