Research On Individual Learning System Based On Data Mining

In order to really realize individualized study' idea that the learners are the principal part in learning, people should Attach importance to the learner characteristic analysis and come true here on the basis learning individuation,The latter is the key technology of individualized study.With the fact that the data mining technology extensive use in education field, Research to ID3 improved algorithm as a hot spot has got broad attention in individualized study field.To utilize the data accumulated about individualized Learning, Classification Rules was researched and ID3 algorithm was improved according to the aracteristic of individualized learning information and a new algorithm called ILIDA-ID3 algorithm is designed based on the ID3 algorithm.. A new individualized learning information data mining model is designed and realized according to practical requirement on the base of ILIDA-ID3 algorithm.The main research works are described as follows:â‘ The paper analyses Parameter that effect individualized Learning, and it puts forward a individualized learning model based on the current student model and IEEE 1484.2 PAPI Model, which describes the learner's personalized information better.â‘¡The ILIDA-ID3 algorithm has the following improvements: (1) According to ID3 algorithm information amounts calculate formula, the paper have brought forward the improvement method. And it has facilitated complicated degree that information amounts calculate and Have improved efficiency of Decision Tree.(2) Correlation degree concept is introduced ILIDA-ID3 algothrim to have all no-classified attributes being analized according correlation degree, and correlation degree threshold is set to delete the attributes which have the correlation degree values below the default threshold.(3)Classification threshold is set to avoid portioning the mined dataset repeatedly.Any dataset with items number less than the classification threshold would not be partitioned any more, instead, a leaf-node is created and the leaf-node would have the classification attribute value which has the largest number of items in the dataset. (4)Complex measure standard is taken to replace information gain to be standard of choosing attribute in ID3 algorithm.â‘¢Based on the ILIDA-ID3 algorithm, individualized learning data mining model has been designed.