| Summary: | 碩士 === 國立中央大學 === 資訊工程研究所 === 88 === Distance learning via Internet becomes more and more popular in recent years. In the asynchronous distance learning environment, students are hard to locate useful information from the large student knowledge database. Teachers’ load increases because of the increasing question from students. The result of searching documents by keyword make students need to examine many documents to get needed ones. Our goals are to establish an knowledge filtering system, find out the documents match a student’s need from the student knowledge database; and to establish a helper finding system, find a expert classmate for the student needs help; and to change the ranking of the searching result to make students reduce the number of times of examine documents.
Based on document feedback from the student, we recommend the student the information from the student knowledge database using k-Nearest Neighbor algorithm. Based on classmate feedback from the student, we recommend the student the expert classmates using Radial Basis Function Network. We take the author of a document into consideration when ranking the searching result.
We establish a learning helper and knowledge finding system based on students’ feedback and student model, it assists students in the asynchronous distance learning environment to find the high quality documents from the student knowledge database; when a student issue a question, it finds a suitable expert classmate to help this student; and it changes the ranking of the searching result to make students reduce the number of times of examine documents.
|
|---|
