Improve Adaptive Learning
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Every student is unique in his own way and has a different way of learning things. Thus, it becomes quite a difficult task for educational organizations to select the methods to adapt in the classroom that will be best for all the students.
Adaptive learning is that the delivery of personalized learning experiences that address the unique needs of people through customized content, real-time feedback, and resources. It seeks to supply a singular yet personalized experience for every user.v
Benefits for the company
Big data can help teachers to discover the abilities of the students and use optimal teaching techniques according to them.
Feasability
High
Type of expertise/ AI domain
Clustering, Segmentation
Internal data required
Student’s Behavioural data, Interaction Data
The mathematics department of Arizona State University has developed a system called “Adaptive Learning” based on the analysis of student data. So that they can take suitable actions for the improvement of student performance.
The developed system collected various data related to students such as their marks, strengths, weaknesses, cultural areas of interest as well as the scenarios in which they hesitate.
The Advisor of ASU combined the information extracted by the system with the registration details and other previous records of the student. This will help them in such a way that they will get a notification whenever the performance of the student starts going off track so that desired actions can be taken before any major harm.
After the implementation of this system, there was a considerable improvement in the success rate of the students and also the dropout rate of students got decreased by around 5.4%.