Personalized Recommendation Service System in E-Learning Using Web Intelligence

Abstract

Abstract. Personalized education is a very hot topic in distant research. To realize personalized E-learning, a personalized recommendation service system was proposed and realized. Web technologies of personality and adaptive filtering were applied in the system. The structure of system, workflow and key technologies of realizing feature selection module, user interest module, personalized teaching resources filtering module were introduced in the paper.

Comparative Study: Feature Selection Methods in the Blended Learning Environment

“…Some of the objectives of classifying are: anticipation of students' successfulness on the basis of data extracted from educational system web log files [11]; identification of students with low level of motivation and detection of appropriate activities in order to decrease ratio of giving up [12]; providing feedback to the students on achieved accomplishments [13]; possibility of directing and recommending learning processes in order to achieve the best results possible [14]; detecting a group of students with similar characteristics and reaction to special educational strategies [15]. There are several studies that dealt with the issue of comparison of classifiers accuracy to the data in the field of education.…”

A Personalized Resource Recommendation System Using Data Mining

“…The web server log records learner's IP address, visiting time, visiting page, visiting way, requested the document URL,HTTP version, return codes, transmission byte, protocol, wrong codes and so on. [3] The model is established according to learner register information. Learner register information is submitted to the system server though Web inputting.…”