A Working Group Construction Mechanism Based on Text Mining and Collaborative Filtering

Abstract

Massive Open Online Courses (MOOCs) are popular in E-learning research domain with the advance of internet technology (Sa'don, Alias, and Ohshima 2014). MOOCs easily provide higher education courses for registered users as well as institutions or teachers who can offer courses in order to join more students than traditional education. However, producing high-quality learning materials may cause increase time, cost and efforts. For the purpose of reusing materials and reducing the cost of re-creating materials, the Learning Object (LO) concepts have been introduced. The content management systems which used these LOs are called Learning Objects Repository (LOR). The stored LOs in the repository can be easily searched by users. In this paper we introduce a working group construction mechanism for users on LOR. The proposed mechanism uses text mining technique to analyse the similarity of groups to construct prototypes of working groups. Then find the users' preferences about LOs based collaborative filtering to optimize constructed prototypes. Hence users on LOR can find quickly and easily their interesting learning materials via relevant working groups. This mechanism reduces the consuming time for re-creating learning materials by improving the quality of production. This study is based on a Google MOOC FRA project (http://googleresearch.blogspot.tw/2015/03/announcing-google-mooc-focused-research.html). There are 3 parts of the system (Fig. 1 (a)) as: conversion tool between ELO (http://edxpdrlab.ncu.cc/), Course Builder, Open edX, and SCORM 2004; Authoring Tool for ELO; and Repository for ELO (Fig. 1 (b)). The user on the ELO repository can access the working groups which related to themselves and reduce the time consumed about re-creating learning materials and improving production quality.