Construction of Online Learner Model Based on Situational Awareness
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Rongqing Zhuo, Zhongxian Bai and Quanjun Lin
With the rapid development of mobile Internet technology, the emergence of the Internet and big data as well as mobile terminals with mobile computer functions. Promoted the transformation of mobile learning personalized services. At the same time, however, in the mobile learning environment with complex online educational resources, the number of learning resources and learning services has increased dramatically, and it has continuously increased the time and effort spent by students on the acquisition and selection of resources. "The problem has greatly affected the efficiency of online learning and the utilization of learning resources. How to effectively use context-aware technology and build a personalized recommendation system is the key to solving the problem of learning resource overload. This has become a research hotspot in the future development of mobile learning. Therefore, this paper introduces context-aware technology, combined with the characteristics of the adaptive learning path recommendation system, from the learner's scenario elements, environmental context elements and application scenarios. Analyze the scenarios that influence the recommendations of the adaptive learning path. The selected scene elements are screened by Delphi method and mathematical statistics method to construct a learner model based on context perception.
Situational Awareness; Online Learning; Adaptive Recommendation; Model Building