Data Mining And Application In MOOC Discussion Forum

Massive open online courses.as a new mode of education for the class, since 2012, with the rise of the three course provider included Coursera, Udacity, edX in US, a wave of online higher education boom quickly set off in the world. MOOC platform with a wide range of audience, high quality of the curriculum, teaching methods and flexible, rich teaching resources are more and more popular with the students.However,precisely because its audience widely distributed and has a huge participant,so the MOOC platform can not pay attention to each learner as well as traditional course.The result is that the enthusastic of learners in MOOC has delined and make the feature of high enrollment and dropout rate among MOOC.People can use data mining methods to asses and analysis MOOC platform’s rich data resources. Through the discussion Area,which can regard as a breakthrough point,we can put forword feasible theory analysis and Application on how to improve the learner’s learning gains.This paper analysis the data that mining from the MOOC’s comments,mainly do the following work:(1) Briefly introduces the bakgound,development and the problems faced by MOOC.(2) By analysing the topic of discussion area in MOOC and design the TEDA algorithm to extract topics from the discussion area.Then propose the TSNC algorithm to establish the topic-based semantic network.(3) To establish the relationship between the learner and the discussion topic and based on the CLPLI algorithm to construct the learning partners according to learning interest.(4) To establish a semantic network by analysing the common betweeen the discussion’s topic and the discussion’s participants.then propose the K.SWN algorithm to navigate in this network.