Concept

Introduction (DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills)

It is very important for the students to efficiently manage their time so that they can learn new concept and retain the previously learned ones. Unfortunately, only few of the colleges and the universities can suggest students efficient structure which would make it possible to achieve both of these goals. In the 19th century testing and spacing methods were proposed and they make it possible to efficiently manage the learning time as well as improve long-term memorization. According to spacing method it is better distributing learning over time than massive learning in order to have long-term retention. Testing (retrieval practice) "basically consists in self-testing after being exposed to new knowledge instead of simply reading the lesson again." The combination of these to can be referred as spaced retrieval practice (temporally distributing tests after the first exposure to the knowledge). Nowadays, researcher have focused on using adaptive and personalized spacing schedulers to improve student learning. Spacing effects have been used in various areas and aren't limited to the vocabulary learning. In this paper the authors aim to create " student learning and forgetting for inferring skills knowledge state and memory dynamics. " As it was described, the authors propose to extend adaptive spacing framework where memorization will focus on the underlying skills. This means that the learner will have the chance to master the set of problems involving that particular skill. They think that this requires new student model which would involve forgetting and learning processes for the multiple skills. This model is called DAS3H .

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Updated 2020-11-03

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Data Science