Right now we are developing an adaptive learning engine which chooses content for each learner individually – by her level and knowledge gaps. The adaptive engine calculate the average difficulty rating based on how many times the students considered the lesson to be too hard or too easy and how quickly and how many attempts on average did it take for a student to complete the assignment.
In the course Adaptive Python you can try out the first prototype of this engine.
If you want to create your own adaptive course, please see our guidance.
The difference between a regular and an adaptive course:
- There is not set structure in an adaptive course.
- A student can not follow a linear pre-set structure of the course, the adaptive engine generates a unique path for each student.
- The students will not get any points upon completing an assignment in an adaptive course. They have skills level and the confidence.
If the course is adaptive, students have extra buttons on the top of the page like this:
The first button becomes active only after students successfully solve the problem. If the problem seems too difficult or too easy, they can click on one of the buttons on the right, the engine will take into account the knowledge level for future content recommendations.
We would be happy to get your feedback on this adaptive system! You can write to us in the comments section below this text ↓ and also below each problem inside the course.
P.S. Initially, the adaptive system may behave somewhat randomly for students, but the more problems they solve, the smarter it becomes!