Research And Application Of Adaptive Learning System Based On Concept Map

With the rapid development of education informatization and education modernization in recent years,the education construction with the theme of smart education is leading the development direction of modern education in China.The continuous advancement and implementation of educational informationization have enabled education to enter the era of big data.The tremendous development of education informatization has promoted the advancement of educational data mining technology,and also put forward higher requirements for educational models and technical levels.The modernization of education has also prompted learners to propose more adaptive learning needs.Current educational techniques and methods have become inadequate in the implementation of modern education.Focusing on how to extract effective information from educational big data,realize adaptive personalized learning goals,and provide teaching ideas and strategic basis for educational informationization,this paper takes the concept map,an important visual evaluation tool in the adaptive learning system,as the research object,and carries out research from the following main aspects:(1)Aiming at the problem that the existing concept map construction method is highly dependent on expert experience and the time-consuming construction of concept maps,this paper proposes an automatic construction model of concept maps based on text classification and association rules mining.The model takes full account of the association attributes between concepts,uses text classification technology in text analysis instead of experts to automatically match concept labels for test questions,and combines association rules mining method to calculate the association between concepts,and automatically constructs some self-adaptive concept maps.This model can reduce the dependence on external expert experience and is of great significance for reducing the construction time of the concept map.At the same time,the concept map constructed in a graphical way clearly shows the association between concepts through the association pair and the relevant degree value,which can provide teaching optimization guidance for knowledge visualization.(2)In order to further develop effective information from the concept map,realize personalized education.This paper fully considers the learning characteristics between different learner groups,and proposes an automatic generation model of learning paths based on concept maps for adaptive learning systems.The model divides learners with different levels of concept mastery into several groups by clustering method,and combines the association rules mining method to construct a number of concept maps with learning characteristics of learners.The topological sorting algorithm is used to continue the analysis of the concept maps,and finally realizes automatic generation of learning paths that conform to the characteristics of adaptive learning systems.This model can overcome the problem of insufficient discrimination ability of learners in current research.Moreover,it can provide guidance for education and further improve the ability of adaptive learning systems based on a variety of teaching plans and suggestions for teaching duration formulated by learning paths.(3)Based on the above research results,from the practical application point of view,a concept map and learning path automatic generation prototype system is designed and developed.The system uses the test questions library and the answer records of the learners collected by the education online platform as the data source,and realizes the two models proposed in this paper,namely the automatic construction model of concept maps and the automatic generation model of learning paths.The generated concept map and learning path are visually displayed in the system through visual tools,providing teachers with measures and basis for improving teaching,and realizing individualized education and teaching of "teaching students according to their aptitude".