AI BASED ADAPTIVE LEARNING

Artificial intelligence (AI) refers to the application of human intelligence in machines that are programmed to think like humans and mimic their actions. Basically the term defines any machine that exhibits traits associated with a human mind such as learning and problem-solving.

Now lets talk about the term Adaptive learning which refers to the delivery of education or training that utilizes technology and data to provide an customized content to learners individually, i.e. intelligently adapting to their learning needs. It is in fact the ability to provide?personalized learning with AI?in educational and corporate sectors. The learning platforms uses computer algorithms, such as Artificial Intelligence and are trained to understand the strengths, weaknesses, learning styles, and proficiency of the student before providing them with the necessary learning material and resources.

Artificial Intelligence with Adaptive Learning

Human intelligence, living conditions, environment – these vary between different learners and are critical in a learners learning cycle. When it comes to education, the conventional idea of a single classroom or one-size-fits-all is rightly losing its luster. People are different and no single learning style is suitable for each one out there. That's where technology, especially AI can help in rendering content that is gathered in a way to reach the need of the learner, either in schools or even in corporate setups. Together with?immersive technologies and AI,?data on individual learners learning pace and ability can be collated in a cost-effective way, and shared to make learning enjoyable, fun and engaging.

When talking about?adaptive learning technology?there are some key ideas to keep in mind:

• The quality of educational content being used
• The ability of the AI based platform to identify, assess and adjust to learners progress
• Tracking progress, measuring performance and leveling up based on results.

Project-based learning, classroom discussion, cooperative learning, and demonstrations, as well as using diverse learning materials, are all examples of methods used in adaptive teaching.

Example for how adaptive learning works and the role of AI with this.

Suppose, during a MCQ based assessment, students in Grade 1 are to name all the cities of India. On completion, the platform would track the answers (right and wrong), grade the test, time spent on it and any other pattern indicated, for each individual student. The data would be stored, and shared with the students/teachers/parents for insights on performance.

The AI and machine learning algorithms in play will then track and analyze the data to interpret the learning style, level of intelligence and other metrics for each student. Based on that, the platform will adjust and upgrade the level of assessment/learning material to be provided to the student, and/or provide recommendations. As such, for the smarter students, Assessment 2 could be based on the landscape of the states, whereas a map-based visual assessment of the same city-state assessment could be shared with the less smarter students.

ADVANTAGES OF AI BASED ADAPTIVE LEARNING

• Saves training resources to minimize the budget.
• Enhances knowledge retention to improve learners' long-lasting skills.
• Boosts learners' engagement to help create a continuous learning culture.
• Increases time efficiency to reduce training time.
• Performs deep analytics to track training efficiency and learners' performance.