Adaptive learning incorporates aspects of machine learning, cognitive science, predictive analytics and educational theory to actively tailor content to each learner’s need
Engage the user for improved learning
Depending on the learner’s engagement level and mastery of the topic, the system can adapt itself. Some of the features of the solution are: Assessment - Depending on the student’s performance on the previous question, the system would adapt itself for subsequent questions; Feedback Mechanism - System will have varied feedback mechanisms that alert students to an error, and guide them back to a previous point in the lesson, or offer hints and tips as to how to resolve the current task; Learning Path – System would move students from one learning path to another depending on the student’ performance on the existing path; and Track individual engagements with the system.
Maximizing learning Efficiency, Effectiveness, Engagement and Retention
Monitor individual student’s performance where they can see which sections they struggled with the most and understand what courses they should take to improve their learning skills
Each student gets their own personalized course, which adjusts in real-time to his or her performance and engagement level
Instructors would be able to create a dynamic assessment system which would create better learning experience for the students
Enables instructors to spend 72% less time on administrative tasks