The slogan of adaptive learning is “ Teach to a student, and not to a class”.

Adaptive e-learning is a learning process in which the content is taught or adapted based on the responses of the students' learning styles or preferences.¹

It done as a computerized method of teaching which tailored resources as personalized for students according to their needs as what they want to learn, learning pathways, and pace of learning. The new AI technology helps advancing the field in recent times. The assessment is also very broad, personalized and quick that keep adapting itself according to the requirement of the students.²

Adaptive learning is a more efficient form of teaching and learning.³

Adaptive technology is traditionally being divided into four 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 – The user interface for interacting with the system

In-time feedback is an integral part of the system, that keeps updating expert, student and its instructional techniques and environments according to students learning capabilities2. A common algorithm is is Bayesian Knowledge Tracing (BKT) which estimates the rate at which learning occurs. Another known framework is Item Response Theory (IRT), developed in the field of psychometrics to model the interaction of a learner with discrete items.4

References:

1. https://doi.org/10.1016/j.compedu.2018.11.005
2. https://en.wikipedia.org/wiki/Adaptive_learning
3. El-Sabagh, H.A. Adaptive e-learning environment based on learning styles and its impact on development students' engagement. Int J Educ Technol High Educ 18, 53 (2021). https://doi.org/10.1186/s41239-021-00289-4
4. https://www.smartsparrow.com/what-is-adaptive-learning/