Adaptive learning has given educators a helping hand to modify their learning strategies to fit all types of learning. It is bringing a completely innovative way education is approached. This new learning style is data-driven and takes a non-linear approach to instruction. Education today is going through a transformation. It isn’t just bringing computers and technology into classrooms, it also how they were being used.
Adaptive learning has the potential to keep students more engaged and to design curricula more responsibly. Adaptive learning products are modelled on different principles with a blend of data science, psychometrics, and machine learning elements and applied in a variety of ways. The objective is to develop the multi-device platform to improve teacher performance, foster student engagement and drive learning success in the classroom. Adaptive learning systems have traditionally been divided into separate components or ‘models’
- Expert model – The model with the information which is to be taught
- Student model – The model which tracks and learns about the student
- Instructional model – The model which actually conveys the information
Instructional environment – Adaptive learning that is implemented in the classroom environment using information technology is often referred to as an Intelligent Tutoring System or an Adaptive Learning System. Intelligent Tutoring Systems operate on three basic principles:
- Systems need to be able to dynamically adapt to the skills and abilities of a student. Inductive Logic Programming (ILP) is a way to bring together inductive learning and logic programming to an Adaptive Learning System.
- Systems must have the ability to be flexible and allow for easy addition of new content.
- Systems need to also adapt to the skill level of the educators.
The key benefits of adaptive learning are:
- Faster and higher quality student progression
- Adapts to different abilities
- Improves understanding
- Engages students
- Allows students to work at different paces
It is emerging educational technology that formalizes it at a much deeper, realistic level through the collection and processing of cognitive and non-cognitive data. It is then used to build learner profiles and evaluate student proficiencies to then enable them to meet their full learning potential.
The adaptive approach allows them to fine tune the instruction and engagement process and the intervention required, making it unique to each individual learner. This impacts the performance of individual students and reduces the gap between the strongest and weakest student. So the learning process becomes more efficient and effective.
About the Author
Dr. Suman Bhattacharya, National Head, Open & Distance Learning has 18 years of experience with seven years in Research & Teaching and eleven years in Industry.