Paper Info
Title
MOOCCubeX: A Large Knowledge-centered Repository for Adaptive Learning in MOOCs
Abstract
ABSTRACTThe prosperity of massive open online courses provides fodder for plentiful research efforts on adaptive learning. However, current open-access educational datasets are still far from sufficient to meet the need for various topics of adaptive learning. Existing released datasets often cover only small-scale data, lack fine-grained knowledge concepts. They are even difficult to curate and supplement due to platform limitations. In this work, we construct MOOCCubeX, a large, knowledge-centered repository consisting of 4,216 courses, 230,263 videos, 358,265 exercises, 637,572 fine-grained concepts and over 296 million behavioral data of 3,330,294 students, for supporting the research topics on adaptive learning in MOOCs. Licensed by XuetangX, one of the largest MOOC websites in China, we obtain abundant and diverse course resources and student behavioral data and are permitted to make subsequent periodic updates. We propose a framework to accomplish data processing, weakly supervised fine-grained concept graph mining, and data curation to improve usability and richness. Based on the fine-grained concepts, we re-organize the data from the knowledge perspective and acquire more external learning resources from the web. Our repository is now available at https://github.com/THU-KEG/MOOCCubeX.
Year
DOI
Venue
2021
10.1145/3459637.3482010
Conference on Information and Knowledge Management
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
19
Name
Order
Citations
PageRank
Jifan Yu102.70
Yuquan Wang200.68
Qingyang Zhong300.68
Gan Luo400.34
Yiming Mao500.34
Kai Sun600.34
Wenzheng Feng731.41
Wei Xu810241.51
Shulin Cao901.35
Kaisheng Zeng1000.68
Zijun Yao1100.68
Hou Lei124919.03
Yankai Lin1301.01
Peng Li1414621.34
Jie Zhou151311.09
Bin Xu1638331.31
Juanzi Li172526154.08
Jie Tang185871300.22
Bin Xu1914328.62