Please wait a minute...
Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (8): 1-8    DOI: 10.11925/infotech.2096-3467.2017.08.01
Orginal Article Current Issue | Archive | Adv Search |
Analyzing Interaction of MOOC Users with Iteration Super Centrality
Wu Jiang(), He Chaocheng, Ma Panhao
School of Information Management, Wuhan University, Wuhan 430072, China
Center of Chinese E-commerce Research and Development, Wuhan University, Wuhan 430072, China
Download: PDF (705 KB)   HTML ( 5
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] This paper evaluates the activity level of the MOOC forum participants and the quality of the forum themes, aiming to improve the participation of the forum users and increase their social impacts. [Methods] We proposed a new concept and algorithm based on “Iterative Super Centricity” with several iterations till convergence. We used nodes of the entire network to determine their importance and influence. [Results] The proposed ISCen (Iterative Super Centrality) algorithm could measure the importance of nodes and their ability to disseminate knowledge. [Limitations] We only examined one course and did not analyze those super-network indicators. [Conclusions] “Iterative Super Centrality” can reveal the activity level of the forum participants and the quality of the online contents, and then improve the MOOC services.

Key wordsMOOC      Forum      Super-network      Iterative Super Centrality      Knowledge Flow     
Received: 31 May 2017      Published: 28 September 2017
ZTFLH:  G434  

Cite this article:

Wu Jiang,He Chaocheng,Ma Panhao. Analyzing Interaction of MOOC Users with Iteration Super Centrality. Data Analysis and Knowledge Discovery, 2017, 1(8): 1-8.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.08.01     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I8/1

超点 v1 v2 v3 v4 v5 v6 v7
初值 2 2 3 2 1 1 1
1次迭代 0.1841 0.219 0.3048 0.0889 0.0857 0.0857 0.0317
2次迭代 0.1821 0.2286 0.317 0.0731 0.0884 0.0884 0.0224
3次迭代 0.1801 0.2333 0.3238 0.0642 0.0905 0.0905 0.0175
4次迭代 0.1787 0.2357 0.3276 0.0594 0.0919 0.0919 0.0149
5次迭代 0.1778 0.2368 0.3296 0.0567 0.0928 0.0928 0.0135
6次迭代 0.1773 0.2374 0.3307 0.0552 0.0933 0.0933 0.0127
7次迭代 0.177 0.2377 0.3314 0.0544 0.0936 0.0936 0.0123
超边 e1 e2 e3 e4 e5
初值 3 2 2 3 2
1次迭代 0.3226 0.1452 0.2339 0.2177 0.0806
2次迭代 0.3369 0.1299 0.2492 0.2266 0.0574
3次迭代 0.3436 0.1205 0.2577 0.2332 0.0451
4次迭代 0.3469 0.1150 0.2622 0.2375 0.0385
5次迭代 0.3485 0.1118 0.2646 0.2402 0.0349
6次迭代 0.3493 0.1101 0.2659 0.2418 0.0329
7次迭代 0.3498 0.1091 0.2666 0.2427 0.0319
用户名 主题1 主题2 主题3 主题4 主题5 主题6
黄如花
Zgg
人在戏中
云层
Vivian2477
小猫钓金鱼
陈岚
Tomcaop
飞沙走石
国际米兰
Arebec
Fakebeast
贝叶树下
用户名 点度 点ISCen
黄如花 6 0.664
Zgg 5 0.509
人在戏中 5 0.509
云层 5 0.503
Vivian2477 4 0.367
小猫钓金鱼 4 0.367
陈岚 4 0.32
Tomcaop 3 0.21
飞沙走石 3 0.171
国际米兰 3 0.214
Arebec 2 0.066
Fakebeast 2 0.091
贝叶树下 2 0.09
主题 边度 边ISCen
主题1 11 2.42
主题2 11 2.49
主题3 9 1.779
主题4 9 1.674
主题5 4 0.318
主题6 4 0.364
[1] 中华人民共和国教育部. 国家中长期教育改革和发展规划纲要(2010-2020年) [EB/OL]. [2010-07-29]. .
[1] (Ministry of Education of the People’s Republic of China. National Medium and Long Term Education Reform and Development Plan (2010-2020年) [EB/OL]. [2010-07- 29].
[2] 汪基德, 冯莹莹, 汪滢. MOOC热背后的冷思考[J]. 教育研究, 2014, 35(9): 104-111.
[2] (Wang Jide, Feng Yingying, Wang Ying.The Cold Thinking Behind MOOC[J]. Educational Research, 2014, 35(9): 104-111.)
[3] 黄如花, 刘龙. MOOC在线交流存在的问题及对策[J]. 图书与情报, 2014(6): 18-22.
[3] (Huang Ruhua, Liu Long.Problems and Countermeasures of Online Communication in MOOC[J]. Library and Information, 2014(6): 18-22.)
[4] Belanger Y, Thornton J.Bioelectricity: A Quantitative Approach-Duke University’s First MOOC[J]. Inorganic Materials, 2013, 38(2): 522-526.
doi: 10.1023/A:1015487425528
[5] Koedinger K R, Kim J, Jia J Z, et al.Learning is Not a Spectator Sport: Doing is Better than Watching for Learning from a MOOC[C]// Proceedings of the 2nd ACM Conference on Learning. 2015: 111-120
[6] Edmunds A, Morris A.The Problem of Information Overload in Business Organizations: A Review of the Literature[J]. International Journal of Information Management, 2000, 20(1): 17-28.
doi: 10.1016/S0268-4012(99)00051-1
[7] Mackness J, Sui F J M, Williams R. The Ideals and Reality of Participating in a MOOC[C]//// Proceedings of the 7th International Conference on Networked Learning.2010.
[8] Skiba D J.Disruption in Higher Education: Massively Open Online Courses (MOOCs)[J]. Nursing Education Perspectives, 2012, 33(6): 416-417.
doi: 10.5480/1536-5026-33.6.416 pmid: 23346794
[9] Siemens G.Connectivism: A Learning Theory for the Digital Age[J]. International Journal of Instructional Technology & Distance Learning, 2005, 2(1): 3-10.
[10] Yang D, Sinha T, Adamson D, et al.“Turn on, Tune in, Drop out”: Anticipating Student Dropouts in Massive Open Online Courses[C]//// Proceedings of the 2013 NIPS Data-Driven Education Workshop. 2013
[11] Jenders M, Krestel R, Naumann F.Which Answer is Best?: Predicting Accepted Answers in MOOC Forums[C]//// Proceedings of the 25th International Conference Companion on World Wide Web. 2016: 679-684.
[12] Chandrasekaran M K, Kan M Y, Bernard C Y T, et al. Learning Instructor Intervention from MOOC Forums: Early Results and Issues[J]. International Educational Data Mining Society, 2015. Article No.: ED560566.
[13] Zhang Q, Peck K L, Hristova A, et al.Exploring the Communication Preferences of MOOC Learners and the Value of Preference-based Groups: Is Grouping Enough?[J]. Educational Technology Research & Development, 2016, 64(4): 809-837.
doi: 10.1007/s11423-016-9439-4
[14] Gillani N, Eynon R.Communication Patterns in Massively Open Online Courses[J]. Internet & Higher Education, 2014, 23(5): 18-26.
doi: 10.1016/j.iheduc.2014.05.004
[15] Newman M E J. The Structure and Function of Complex Networks[J]. SIAM Review, 2003, 45(2): 167-256.
doi: 10.1137/S003614450342480
[16] Nagurney A, Dong J.Supernetworks: Decision-Making for the Information Age[M]. Elgar, Edward Publishing, 2002.
[17] Holme P, Liljeros F, Edling C R, et al. Network Bipartivity[J]. Physical Review E: Statistical Nonlinear & Soft Matter Physics, 2003, 68(2): Article No. 056107.
[18] Liljeros F, Edling C R, Lan A.The Web of Human Sexual Contacts[J]. Nature, 2001, 411(6840): 907.
doi: 10.1038/35082140 pmid: 11418846
[19] Liljeros F, Edling C R, Amaral L A N. Sexual Networks: Implications for the Transmission of Sexually Transmitted Infections[J]. Microbes & Infection, 2003, 5(2): 189-196.
doi: 10.1016/S1286-4579(02)00058-8 pmid: 12650777
[20] Jeong H, Tombor B, Albert R, et al.The Large-scale Organization of Metabolic Networks[J]. Nature, 2000, 407(6804): 651-654.
doi: 10.1038/35036627
[21] Corsini P, Leoreanu V.Graphs and Hypergraphs[A]// Applications of Hyperstructure Theory[M]. Springer US, 2003: 127-139.
[22] 漆玉虎, 郭进利, 王志省. 超网络度参数研究[J]. 科技与管理, 2013, 15(1): 34-38.
doi: 10.3969/j.issn.1008-7133.2013.01.008
[22] (Qi Yuhu, Guo Jinli, Wang Zhisheng.Research on the Degree of Hypernetwork[J]. Science-Technology and Management, 2013, 15(1): 34-38.)
doi: 10.3969/j.issn.1008-7133.2013.01.008
[23] 胡枫, 赵海兴, 马秀娟. 一种超网络演化模型构建及特性分析[J]. 中国科学: 物理学力学天文学, 2013, 43(1): 16-22.
doi: 10.1360/132012-87
[23] (Hu Feng, Zhao Haixing, Ma Xiujuan.An Envolving Hypernetwork Model and It’s Properties[J]. Science in China: Series G, 2013, 43(1): 16-22.)
doi: 10.1360/132012-87
[24] 吴江, 马磐昊. 基于超网络的MOOC平台知识流动研究[J]. 图书与情报, 2015(6): 97-106.
doi: 10.11968/tsyqb.1003-6938.2015134
[24] (Wu Jiang, Ma Panhao.Knowledge Flow Research in MOOC Platform Based on Super Network[J]. Library and Information, 2015(6): 97-106.)
doi: 10.11968/tsyqb.1003-6938.2015134
[25] 柳俊, 周斌, 黄九鸣. 基于二部图投影的微博事件关联分析方法研究[J]. 信息网络安全, 2014(9): 44-49.
[25] (Liu Jun, Zhou Bin, Huang Jiuming.Research on Microblogging Event Correlation Analysis Method Based on Bipartite Graph Projection[J]. Netinfo Security, 2014(9): 44-49.)
[26] Alariohoyos C, Perezsanagustin M, Delgadokloos C, et al.Delving into Participants’ Profiles and Use of Social Tools in MOOCs[J]. IEEE Transactions on Learning Technologies, 2014, 7(3): 260-266.
doi: 10.1109/TLT.2014.2311807
[27] Zhan Z, Fong P S W, Mei H, et al. Sustainability Education in Massive Open Online Courses: A Content Analysis Approach[J]. Sustainability, 2015, 7(3): 2274-2300.
doi: 10.3390/su7032274
[1] Xu Guang,Ren Ming,Song Chengyu. Extracting China’s Economic Image from Western News[J]. 数据分析与知识发现, 2021, 5(5): 30-40.
[2] Pengcheng Xu,Qiang Bi. Identifying Domain Experts Based on Knowledge Super-Network[J]. 数据分析与知识发现, 2019, 3(11): 89-98.
[3] Ding Shengchun,Liu Menglu,Fu Zhu. Unified Multidimensional Model Based on Knowledge Flow in Conceptual Design[J]. 数据分析与知识发现, 2018, 2(2): 11-19.
[4] Wang Yuefen,Fu Zhu,Wu Peng. Tech-Framework for Semantic Knowledge Management in Conceptual Design[J]. 数据分析与知识发现, 2018, 2(2): 2-10.
[5] Lu Xiaohang,Wang Shengqing,Huang Junjie,Chen Wenguang,Yan Zengwang. Predicting Dropout Rates of MOOCs with Sliding Window Model[J]. 数据分析与知识发现, 2017, 1(4): 67-75.
[6] Wang Yuefen,Fu Zhu,Chen Bikun. Analyzing Knowledge Structure Research with LDA Model[J]. 现代图书情报技术, 2016, 32(4): 8-19.
[7] Lan Qiujun,Liu Wenxing,Li Weikang,Hu Xingye. Sentiment Analysis of Financial Forum Textual Message[J]. 现代图书情报技术, 2016, 32(4): 64-71.
[8] Li Zhiyi,Huang Chengye. A Design and Implementation of Webbased Forum[J]. 现代图书情报技术, 2004, 20(1): 88-90.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn