Adaptive Learning - What, How, Why, and more…

Every student has different learning needs because the intelligence quotient of every student is different. Someone might be capable of learning three chapters in a day, while someone else might get stuck on the first topic itself! That is why adaptive learning technology is used to match the learning pace of individual students.

Adaptive learning solutions have many benefits. However implementing them requires a culmination of Artificial Intelligence and Machine Learning algorithms, which are tricky and require intensive training.

So, if you intend to know more about Adaptive Learning technology, how it can be implemented, what are its benefits, and everything else, this blog is for you. Let’s get started!

In adaptive learning, the courses can “adapt” themselves to the pace and learning needs of the individual learners. In a way, you can say that these courses are customized to cater to the specific needs of the learners.

Technically, adaptive learning platforms rely heavily on machine learning and artificial intelligence. These AI and ML algorithms are capable of scrutinizing the entire learning trajectory of the learners in real time.

So, when the student learns a new topic, multiple questions are asked to him at frequent intervals. Based on his responses, the system decides his pace of learning and customizes the course as per his level of understanding. Let’s take a look at the working of adaptive learning in detail.

Adaptive Learning works on the basis of the response it receives from its learners! Actually, these responses act as a training data set for the underlying ML algorithm, that forms the base of any adaptive learning platform.

Now you may ask, what’s so complicated in it? It is the algorithm that is being used!

Adaptive learning systems operate on a special set of Machine Learning algorithms called Adaptive Machine Learning (or Adaptive ML). Its operation is somewhat similar to Reinforcement Learning.

Adaptive ML specializes in collecting real-time data from the users, analyzing it, and delivering the output in real-time. It does not have a pre-determined data set as supervised and unsupervised learning.

So, when the students enter the responses in the form of answers to the questions, they act as data for the algorithm. The algorithm gathers this data and passes it through the adaptation engine, which essentially comprises an adaptive navigation engine and a recommendation system.

The adaptation engine recommends the best-suited lesson for the learner based on the response given. So, the learner gets to learn the recommended topic, which helps them clear their previous doubts. Hence, they are not forced to learn new topics without understanding the previous topics completely.

Adaptive learning is the need of the hour, as it focuses on delivering student-centric learning courses, that can fill all the learning gaps of the learners. It has multiple benefits for the students, some of which are listed below.

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