An Intelligent Procedure for Dynamic Evaluation in a Scientific Learning Session

Abstract

In this research, we are interested in the evaluation of scientific subjects' teaching components such as course questions, examples, application and deepening exercises. Thereby, we have presented a method that allows the teacher to make decisions using a system that implements interpretations based on the decision tree. The proposed system does not only propose assessing students' learning, but it also offers the teacher intervention phases to reduce the difficulties encountered by students. This evaluation approach offers the opportunity for each student to acquire the necessary skills needed in their learning according to their abilities. In our research, we are interested in an evaluation that is based on an intelligent strategy to adjust the students learning during the classroom session. We present the interaction strategy between the teacher, the intelligent system and the students. Last but not least, we build the decision tree and interpret the results obtained, its use by the teacher for any further improvement. Consequently, this indicates the importance of this evaluation conception through artificial intelligence and its impact on machine learning by offering it an interesting database.