Abstract: Education goals include cognitive domain goal,motor skill domain goal and emotional domain goal.Education of emotional domain goal has received attentions and research of more and more pedagogues and scholars of many domains.Emotions of learners play an important role in traditional education and network education,and they affect lear-ning initiative,enthusiasm,creativity and learning effects of learners.According to authors’ teaching practices of algorithm related courses of undergraduates and master graduates for many years,this paper built a fine-granularity learning emotion ontology,and proposed a learning effect evaluation method based on fine-granularity learning emotion ontology.The characteristics of the fine-granularity learning emotion ontology are that it introduces multiple semantic relations among knowledge points of courses,and constructs a classification of emotion feedback actions of teachers.The traits of the learning effect evaluation method are that it builds the evolutional model of learning emotion based on relational paths of knowledge points in the fine-granularity learning emotion ontology,and this model can be used to evaluate learning effects of learners.

Key words: Algorithm course, Evolutional model of learning emotion, Fine-granularity learning emotion ontology, Learning effect evaluation