Studies on the Construction of Online Learning Adaptive Intervention Strategy Library

Online learning is the main implementation of distance education and adult education. A pertinence and timely online teaching intervention could determine the persistence and quality of online learning. However, the existing intervention mechanism is mainly determined by teachers and focus on offline intervention which cannot be compatible with the online learning system well. In this paper we propose a model of online intervention which based on the learning behavior features. After interveners selection, the adaptive intervention measures could be generated in the intervention strategy library and executed automated. We emphasis on the construction of the intervention strategy library which combines with historical intervention experiences in strategy forming and representation. Besides this, we take a decision-making algorithm to classify the strategies and make adaptive and accurate strategies to different kinds of interveners. Adaptive online intervention strategy library is the premise and basis of automated online intervention, which can reduce the gap between the large number of online learners and the limited number of teachers. It also can improve the awareness of learners and teachers, thus gain the better effect on online learning ultimately.