Online Small Sample Learner Modeling and Curriculum Recommendation with Healthy Emotional Factors of College Students

Online education is a popular way for college students at present, and it is also a good compensation way to meet the special situation that traditional offline teaching cannot complete the teaching task. Traditional classroom teaching methods have been difficult to meet the learning requirements of contemporary college students, while online classroom has made up for the shortcomings of traditional classroom teaching to some extent because of its short class hours, prominent focus, and online mobile learning. First, this paper proposes an online SSL (small sample learner) model for college students to integrate healthy emotional factors. The characteristics of learners are divided into three categories: basic characteristics of learners, characteristics of behavioral factors, and characteristics of emotional factors, and the problem of solving mapping functions is transformed into the problem of solving kernel functions. Second, a novel curriculum recommendation model integrating healthy emotional factors is proposed, which fully considers the influence of user comments on similarity and transforms the similarity of users in the overall score of the project into the similarity of users in the emotional tendency of the special attributes of the project. Through the experimental evaluation, the accuracy and stability of the recommendation are greatly improved.