A Course Recommendation System Oriented to Multiple Condition Constraints

Abstract

E-Learning recommendation is an important application in the Self-Adopting Learning. The recommendation problem in the education field is special, and it cannot be separated from subjective factors such as students' preference, expectations of performance and so on. The target of e-learning recommendation should be to enhance students' learning enthusiasm. In this work, we propose a novel course recommendation method for learners with multiple objectives and constraints. This method achieves the purpose of recommendation by generating a recommended course list, and employs the genetic algorithm to balance the constraints between various conditions to optimize the generated recommended course list. Experiments confirm that our approach has more advantages than baselines oriented to multiple constraints.