Thread structure prediction for MOOC discussion forum

Chengjie Sun; Shang Wen Li; Lei Lin

doi:10.1007/978-981-10-2098-8_13

Thread structure prediction for MOOC discussion forum

Chengjie Sun^*
, Shang Wen Li
, Lei Lin

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology
Massachusetts Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

Discussion forums are an indispensable interactive component for Massive Open Online Courses (MOOC). However, the organization of current discussion forums is not well-designed. Trouble-shooting threads are valuable for both learners and instructors, but they are drowned out in the forums with huge amounts of threads. This work first built a labeled data set for trouble-shooting thread structure prediction by crowdsourcing and then proposed methods for trouble-shooting thread detection and thread structure prediction on the data set. The output of this work can be used to spot trouble-shooting threads and show them along with structure tags in MOOC discussion forums.

Original language	English
Title of host publication	Social Computing - 2nd International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, Proceedings
Editors	Wanxiang Che, Hongzhi Wang, Weipeng Jing, Guanglu Sun, Xianhua Song, Zeguang Lu, Qilong Han, Junyu Lin, Hongtao Song, Shaoliang Peng
Publisher	Springer Verlag
Pages	92-101
Number of pages	10
ISBN (Print)	9789811020971
DOIs	https://doi.org/10.1007/978-981-10-2098-8_13
State	Published - 2016
Externally published	Yes
Event	2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016 - Harbin, China Duration: 20 Aug 2016 → 22 Aug 2016

Publication series

Name	Communications in Computer and Information Science
Volume	624
ISSN (Print)	1865-0929

Conference

Conference	2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016
Country/Territory	China
City	Harbin
Period	20/08/16 → 22/08/16

Keywords

Crowdsourcing
Lightly supervised learning
MOOC
Thread structure prediction

Access to Document

10.1007/978-981-10-2098-8_13

Cite this

Sun, C., Li, S. W., & Lin, L. (2016). Thread structure prediction for MOOC discussion forum. In W. Che, H. Wang, W. Jing, G. Sun, X. Song, Z. Lu, Q. Han, J. Lin, H. Song, & S. Peng (Eds.), Social Computing - 2nd International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, Proceedings (pp. 92-101). (Communications in Computer and Information Science; Vol. 624). Springer Verlag. https://doi.org/10.1007/978-981-10-2098-8_13

Sun, Chengjie ; Li, Shang Wen ; Lin, Lei. / Thread structure prediction for MOOC discussion forum. Social Computing - 2nd International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, Proceedings. editor / Wanxiang Che ; Hongzhi Wang ; Weipeng Jing ; Guanglu Sun ; Xianhua Song ; Zeguang Lu ; Qilong Han ; Junyu Lin ; Hongtao Song ; Shaoliang Peng. Springer Verlag, 2016. pp. 92-101 (Communications in Computer and Information Science).

@inproceedings{d6346db1582c4b9a8969693250eb1587,

title = "Thread structure prediction for MOOC discussion forum",

abstract = "Discussion forums are an indispensable interactive component for Massive Open Online Courses (MOOC). However, the organization of current discussion forums is not well-designed. Trouble-shooting threads are valuable for both learners and instructors, but they are drowned out in the forums with huge amounts of threads. This work first built a labeled data set for trouble-shooting thread structure prediction by crowdsourcing and then proposed methods for trouble-shooting thread detection and thread structure prediction on the data set. The output of this work can be used to spot trouble-shooting threads and show them along with structure tags in MOOC discussion forums.",

keywords = "Crowdsourcing, Lightly supervised learning, MOOC, Thread structure prediction",

author = "Chengjie Sun and Li, \{Shang Wen\} and Lei Lin",

note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media Singapore 2016.; 2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016 ; Conference date: 20-08-2016 Through 22-08-2016",

year = "2016",

doi = "10.1007/978-981-10-2098-8\_13",

language = "英语",

isbn = "9789811020971",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "92--101",

editor = "Wanxiang Che and Hongzhi Wang and Weipeng Jing and Guanglu Sun and Xianhua Song and Zeguang Lu and Qilong Han and Junyu Lin and Hongtao Song and Shaoliang Peng",

booktitle = "Social Computing - 2nd International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, Proceedings",

address = "德国",

}

Sun, C, Li, SW & Lin, L 2016, Thread structure prediction for MOOC discussion forum. in W Che, H Wang, W Jing, G Sun, X Song, Z Lu, Q Han, J Lin, H Song & S Peng (eds), Social Computing - 2nd International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, Proceedings. Communications in Computer and Information Science, vol. 624, Springer Verlag, pp. 92-101, 2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, Harbin, China, 20/08/16. https://doi.org/10.1007/978-981-10-2098-8_13

Thread structure prediction for MOOC discussion forum. / Sun, Chengjie; Li, Shang Wen; Lin, Lei.
Social Computing - 2nd International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, Proceedings. ed. / Wanxiang Che; Hongzhi Wang; Weipeng Jing; Guanglu Sun; Xianhua Song; Zeguang Lu; Qilong Han; Junyu Lin; Hongtao Song; Shaoliang Peng. Springer Verlag, 2016. p. 92-101 (Communications in Computer and Information Science; Vol. 624).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Thread structure prediction for MOOC discussion forum

AU - Sun, Chengjie

AU - Li, Shang Wen

AU - Lin, Lei

N1 - Publisher Copyright: © Springer Science+Business Media Singapore 2016.

PY - 2016

Y1 - 2016

N2 - Discussion forums are an indispensable interactive component for Massive Open Online Courses (MOOC). However, the organization of current discussion forums is not well-designed. Trouble-shooting threads are valuable for both learners and instructors, but they are drowned out in the forums with huge amounts of threads. This work first built a labeled data set for trouble-shooting thread structure prediction by crowdsourcing and then proposed methods for trouble-shooting thread detection and thread structure prediction on the data set. The output of this work can be used to spot trouble-shooting threads and show them along with structure tags in MOOC discussion forums.

AB - Discussion forums are an indispensable interactive component for Massive Open Online Courses (MOOC). However, the organization of current discussion forums is not well-designed. Trouble-shooting threads are valuable for both learners and instructors, but they are drowned out in the forums with huge amounts of threads. This work first built a labeled data set for trouble-shooting thread structure prediction by crowdsourcing and then proposed methods for trouble-shooting thread detection and thread structure prediction on the data set. The output of this work can be used to spot trouble-shooting threads and show them along with structure tags in MOOC discussion forums.

KW - Crowdsourcing

KW - Lightly supervised learning

KW - MOOC

KW - Thread structure prediction

UR - https://www.scopus.com/pages/publications/84982899690

U2 - 10.1007/978-981-10-2098-8_13

DO - 10.1007/978-981-10-2098-8_13

M3 - 会议稿件

AN - SCOPUS:84982899690

SN - 9789811020971

T3 - Communications in Computer and Information Science

SP - 92

EP - 101

BT - Social Computing - 2nd International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, Proceedings

A2 - Che, Wanxiang

A2 - Wang, Hongzhi

A2 - Jing, Weipeng

A2 - Sun, Guanglu

A2 - Song, Xianhua

A2 - Lu, Zeguang

A2 - Han, Qilong

A2 - Lin, Junyu

A2 - Song, Hongtao

A2 - Peng, Shaoliang

PB - Springer Verlag

T2 - 2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016

Y2 - 20 August 2016 through 22 August 2016

ER -

Sun C, Li SW, Lin L. Thread structure prediction for MOOC discussion forum. In Che W, Wang H, Jing W, Sun G, Song X, Lu Z, Han Q, Lin J, Song H, Peng S, editors, Social Computing - 2nd International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, Proceedings. Springer Verlag. 2016. p. 92-101. (Communications in Computer and Information Science). doi: 10.1007/978-981-10-2098-8_13

Thread structure prediction for MOOC discussion forum

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Keywords

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