Skip to main navigation Skip to search Skip to main content

Education data mining: How to mine interactive text in MOOCs using natural language process

  • Harbin University of Commerce

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a combination of data mining and natural language processing technology, try to analyze students' learning behavior and content in MOOCs interactive part, to dig their learning interest, difficulty, tendencies, to evaluate their homework effect, through the interaction between teachers and students, students posting, homework or answer content, preventing of cheating behavior, and so on. So that, teachers optimize the course structure, establish of incentive mechanisms to stimulate students' learning desire, improve the completion rate of the courses. This method can dig valuable information from the seemingly random mass data, optimize the corresponding key elements in the teaching model, so that, teaching works go in a virtuous circle.

Original languageEnglish
Title of host publicationICCSE 2017 - 12th International Conference on Computer Science and Education
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages694-699
Number of pages6
ISBN (Electronic)9781509025084
DOIs
StatePublished - 26 Oct 2017
Externally publishedYes
Event12th International Conference on Computer Science and Education, ICCSE 2017 - Houston, United States
Duration: 22 Aug 201725 Aug 2017

Publication series

NameICCSE 2017 - 12th International Conference on Computer Science and Education

Conference

Conference12th International Conference on Computer Science and Education, ICCSE 2017
Country/TerritoryUnited States
CityHouston
Period22/08/1725/08/17

Keywords

  • Data mining
  • Interactive text
  • MOOCs
  • NLP

Fingerprint

Dive into the research topics of 'Education data mining: How to mine interactive text in MOOCs using natural language process'. Together they form a unique fingerprint.

Cite this