Interest Preference Information Mining for Online Learning

With the advent of the Internet era, network technology has gradually been applied to education and teaching. The teaching method of online learning, as a derivative of the new teaching model, promotes the development and transformation of traditional education and teaching. Because each student has...

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Bibliographic Details
Published in2019 10th International Conference on Information Technology in Medicine and Education (ITME) pp. 409 - 414
Main Authors Song, Yongqiang, Wang, Hong, Chu, Qian
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2019
Subjects
Conferences
Education
Information technology
Online Learning
Student Behavior
Student Type
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Summary:With the advent of the Internet era, network technology has gradually been applied to education and teaching. The teaching method of online learning, as a derivative of the new teaching model, promotes the development and transformation of traditional education and teaching. Because each student has different learning focus areas and behaviors, it is the research direction of online learning to analyze the learning characteristics of specific students. This paper firstly divides the user type by clustering algorithm, uses the eye movement experiment to obtain the user behavior data, analyzes the data and finds the students' interest areas, which helps the online learning system to formulate specific learning strategies according to different users.
ISSN:2474-3828
DOI:10.1109/ITME.2019.00098