@inproceedings{f760d56721ba428e80829371fb53bb07,
title = "Learning quality evaluation of MOOC based on big data analysis",
abstract = "The popularity of Massive Open Online Courses has been rapidly growing recently. However, the completion rates of MOOC appear to be quite low. Moreover, the learning quality is quite doubtful for administrators of Universities since there is no suitable tools to evaluate it. Benefitting from the online environment, MOOC platforms can collect and store a huge amount of data related to learning processes. We use Storm as the parallel computing tool to accomplish the data analysis of MOOC. Our research focuses on three types of learning quality evaluation: relationship between students{\textquoteright} forum participation and their academic performance, relationship between students{\textquoteright} forum emotion and their academic performance, relationship between students{\textquoteright} video seeking operation and their academic performance.",
keywords = "Big data analysis, Learning quality evaluation, MOOC",
author = "Zihao Zhao and Qiangqiang Wu and Haopeng Chen and Chengcheng Wan",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 1st International Conference on Smart Computing and Communication, SmartCom 2016 ; Conference date: 17-12-2016 Through 19-12-2016",
year = "2017",
doi = "10.1007/978-3-319-52015-5\_28",
language = "英语",
isbn = "9783319520148",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "277--286",
editor = "Meikang Qiu",
booktitle = "Smart Computing and Communication - 1st International Conference, SmartCom 2016, Proceedings",
address = "德国",
}