Research On Adaptive Engine In Personalized Learning

The 13 th Five-Year Plan for Education Informationization released by the Ministry of Education in 2016 pointed out that by 2020,the national education modernization goal of “everyone can learn,everywhere can learn,and always can learn” is basically established.Personalized learning is one of the prominent advantages of education informatization.Providing suitable learning contents,test contents and presentation modes for different learners based on their learning states,recommending adaptive learning ways based on learners' cognitive level are two core problems in personalized learning.The thesis takes adaptive engine as the main research content,uses rule engine technology to provide decision support for adaptive engine,and uses adaptive engine content self-adaptation and knowledge navigation self-adaptation to explore the application of adaptive engine in personalized learning environment.A new type of adaptive engine architecture is proposed,designed,verified and implemented by using a personalized learning support system.The thesis includes the following aspects:The learner model and domain knowledge model are the research foundations of the adaptive engine.The thesis studies and analyzes these two models firstly.This study divides the construction of learner models into dynamic and static parts.In order to achieve the sharing of the model,this thesis improves the construction specification of the model.Based on the requirements of related constraints and adaptability engines,the thesis proposes the design principles of the model and gives the structure of the model.Then,the thesis makes use of the separation of business decision-making and technology in the rules engine technology to solve the maintenance problems caused by the frequent change of strategies in the personalized learning environment.The thesis uses the rules engine as the decision analysis component to process the decision-making process for the adaptive engine.In order to solve the problem of unreasonable order of rules and the large memory space,the thesis proposes a method of pre-regulation and fact indexing to optimize and improve the RETE algorithm and verifies the improved rule matching efficiency.Finally,in the context of personalized learning,the thesis divides the function of the adaptive engine into content presentation function,knowledge navigation function and model maintenance function,and then describes the structure and work flow of each functional component,gives the function modules of each part,and explains how it works.Based on the adaptive engine,the design scheme of the system is proposed and applied in the network English teaching system.The feasibility of the proposed scheme is verified.