Research On The Construction And Application Of Smart Learning Model Supported By Artificial Intelligence

"Who to educate,how to educate and for whom to educate" is the fundamental issue and eternal theme of education.Education is the great plan of the country,the great plan of the party,and the important cornerstone of national rejuvenation and social progress.Education shoulders the important mission of cultivating innovative talents for the great rejuvenation of the Chinese nation.Teaching students according to their aptitude,integrating knowledge with practice and developing wisdom have always been the ideal pursuit in the field of education.In recent years,with the rapid development of artificial intelligence technology represented by knowledge graph and deep learning,it has provided an opportunity for educational innovation and learning mode reform.How to use intelligent technology to promote learners’ smart learning has become one of the important topics in the field of education.Smart learning,as a new learning method with deep integration of intelligent technology,learning content and learning services,is of great significance in cultivating learners’ key abilities in disciplines and promoting their diversified development of wisdom.The realization of smart learning is inseparable from the strong support of smart learning model.Building a smart learning model with complete structure,clear characteristics and clear logic is an important challenge for the implementation of smart learning.As a basic subject in the stage of basic education,primary school mathematics is of great significance to cultivate students’ abstract thinking,reasoning ability,innovation ability and problem-solving ability.How to build a smart learning model with the help of intelligent technology,design an effective smart learning environment based on the model,help learners to carry out smart learning in the primary school mathematics curriculum,and cultivate the key ability of the subject is a problem worthy of in-depth study.This study aims at the bottleneck problems of constructing smart learning model,such as the difficulty of systematic,complete and accurate quantitative representation of secondary school ability goals,the difficulty of obtaining learning behavior data,and the lack of cultivation of learners’ problem-solving ability and creative thinking ability,this study focuses on the core theme of " how to promote learners’ smart learning with the support of artificial intelligence ",takes primary school mathematics as the carrier,and uses literature research method,questionnaire survey method,Delphi method Quasi experimental method and other research methods,from the aspects of smart learning model structure determination,discipline knowledge graph design,smart learning engine implementation,application effect verification,etc.,the specific research work is as follows:First,the research on the overall structure of smart learning model.Aiming at the problem of "how to build a smart learning model that can quantitatively represent subject ability objectives,accurately describe the level of learners,and personalize recommended learning services",this study built a smart learning E-GPPE-C model with the support of artificial intelligence.First of all,through the combination of literature analysis and expert consultation,this study refine the six elements of smart learning model.Secondly,using reigeluth model construction method and Delphi method for reference,this study constructs the smart learning E-GPPE-C model through the steps of model initial construction,model cycle correction,model establishment and so on.Finally,this study describes the three operating mechanisms of smart learning EGPPE-C model,including the six core elements of learning environment,subject knowledge graph,learner portrait,learning path,learning evaluation and learning community,as well as the five layer structure of foundation layer,support layer,service layer,key layer and application layer.The research on the structure of smart learning model provides the foundation and basis for the construction of subject knowledge graph,the portrayal of learners’ portraits,the recommendation of learning services and the verification of application effects.Second,the research on the construction of subject knowledge graph.Aiming at the problem of "how to quantitatively represent the goal of subject ability in smart learning",this study uses knowledge graph technology to build a subject knowledge graph with primary school mathematics as an example.First of all,from the theoretical evidence,technical support and practical needs of this study,this study puts forward the basis for the construction of disciplinary knowledge graph.Secondly,this study proposes a knowledge graph structure including knowledge diagram,problem diagram and ability diagram.Then,through literature analysis and Delphi method,this study designs the primary school mathematics knowledge cluster,problem set and ability base.The knowledge cluster includes 3 first-class knowledge topics and 88 core concepts,the problem set includes 5 problem topics and 105 core problems,and the ability base includes 5 key abilities and 14 sub item abilities.Finally,this study proposes the implementation method of subject knowledge atlas from four aspects: data acquisition,knowledge extraction,knowledge fusion and knowledge reasoning.The subject knowledge graph can accurately depict the subject ability through problem solving,quantify and characterize the goal of subject ability,and provide the basis for the smooth development of smart learning.Third,the research on learner portrait and learning service recommendation.Aiming at the problem of "how to accurately depict learner portraits and recommend learning services",this study proposes the implementation methods of learners’ portraits depiction and learning services recommendation based on the subject knowledge graph.In this study,a learner portrait construction method based on subject knowledge graph and big data computing analysis is proposed,a learning path recommendation method based on subject knowledge graph and swarm intelligence optimization algorithm is proposed,a learning evaluation method based on subject knowledge graph and deep learning is proposed,and a learning community construction method based on subject knowledge graph and clustering algorithm is proposed.The implementation methods of learner portrait depiction and learning service recommendation provide a basis for the design and implementation of smart learning system.Fourth,the research on application effect verification.Aiming at the problem of "how to verify the effectiveness of the smart learning model",this study applies the smart learning e-gppe-c model to the cloud integrated smart learning system in S Park,and uses the quasi experimental research method to verify the application effect of the system for a semester.Through the analysis of the experimental data,the following conclusions are drawn:(1)Smart learning system helps to improve students’ academic performance;(2)Smart learning system helps to improve the satisfaction of learning environment;(3)Smart learning system helps to improve students’ problem-solving ability;(4)Smart learning system helps to improve students’ creative thinking ability.This study provides a basis for the application of artificial intelligence in the field of education and the development of smart learning,and provides a reference for the follow-up study of smart learning model.