Student Frustration Level Estimation Using Machine Learning

Computer Engineering

Most of the time students often get frustrated due to long class hours and hectic schedule in the academic process. To maintain their enthusiasm up it always needs to motivate them in the right direction, otherwise the student may end up failing in the exams and in turn it may yield in discontinuation of the current education . There are no particular methodologies are existed to measure their frustration level so that right action can be taken to boost them up. Some finger counting methodologies are existed which are used to measure the frustration level by using some data mining techniques. So to boost the level of precision proposed model uses the student's behavior by providing some tests. The scores of these tests are used in the machine learning process using Decision tree to evaluate the frustration level of the student. Based on this frustration level, proposed model displays some motivational suggestions to the student to come out of the current frustration level.

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