A Learning Ability Evaluation Method Based On Item Response Theory and Machine Learning Method

Abstract

In recent years, online education and MOOC (Massive Open Online Courses) education have arisen. This paper proposes a learner ability modeling method based on item response theory and machine learning method. We use item response theory to calculate intermediate parameters and use machine learning to predict learners' learning ability after learning a new course. At the same time, this paper also presents a solution to the cold start problem. Compared to the traditional machine learning prediction method, the models of this paper have certain advantages for the learning ability prediction method.