博碩士論文 100522092 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:10 、訪客IP:3.138.141.202
姓名 王舜楷(Shun-Kai, Wang)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 建基於開放式網路社群學習環境之社群推薦機制
(A Social Recommendation Mechanism for Online OpenCourseWare Environment)
相關論文
★ 基於edX線上討論板社交關係之分組機制★ 利用Kinect建置3D視覺化之Facebook互動系統
★ 利用 Kinect建置智慧型教室之評量系統★ 基於行動裝置應用之智慧型都會區路徑規劃機制
★ 基於分析關鍵動量相關性之動態紋理轉換★ 基於保護影像中直線結構的細縫裁減系統
★ 英語作為外語的互動式情境學習環境之系統設計★ 基於膚色保存之情感色彩轉換機制
★ 一個用於虛擬鍵盤之手勢識別框架★ 分數冪次型灰色生成預測模型誤差分析暨電腦工具箱之研發
★ 使用慣性傳感器構建即時人體骨架動作★ 基於多台攝影機即時三維建模
★ 基於互補度與社群網路分析於基因演算法之分組機制★ 即時手部追蹤之虛擬樂器演奏系統
★ 基於類神經網路之即時虛擬樂器演奏系統★ 即時手部追蹤系統以虛擬大提琴為例
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 「社群學習」是人類最自然的一種學習方式,透過觀察、模仿其他人的行為,以及實際參與了活動與其他人互動、交流,從這一連串的社交過程之中建立了認知、經驗以及記憶,這些最後都為成為我們所學習的知識。在近十幾年來,數位學習因為網路科技的快速發展而大放異彩,數位學習系統如雨後春筍般的出現。然而,當前的數位學習系統大多只是扮演輔助學習的角色,例如提供教材或是學習資訊,提供教師與學生或是學生之間溝通、討論的管道或平台是比較少見且能力有限,因此當今的數位學習系統仍無法完全的支援社群學習的環境。近年來,社群網站的快速發展,每個人每天都會在社群網站上和其他人互動、交流,使得社群網站已成為現代人不可或缺的元素之一,這也使得一些與社會學相關的研究領域開始研究社群網路所帶來的影響,數位學習與社群學習也在其中之一,許多研究都在探討社群網路以及社群網站能為數位學習系統帶來什麼樣的新風貌與新格局。
近年來,「開放式網路課程」在數位學習領域掀起一陣風潮,使用者只需要在網站上註冊一個帳號,即可從網路上獲得世界各大知名大學提供的高等教育課程來進行自主學習。開放式網路課程除了如一般遠距數位學習系統一樣打破了時空的限制,同時也打破了教室與學校的限制,使得在網路學校/網路大學成為教育學界一個新的理念,甚至有知名大學願意為開放式網路課程提供學分的認證。由於其純網路的自主學習環境缺乏了教師的指導以及建議,使得如何讓學生取得適當的教材成為了一個很重要的議題;同時,純網路的學習環境中所形成的學習社群如何為學生的學習成效加分,社群與同儕學習的互動學習機制也成為系統設計的一個研究重點。
本研究中我們將現行使用之社群網站與數位學習系統做整合,透過社群網路的力量來提供一個開放式網路課程的社群學習環境。同時自數位學習系統中取得學生的學習歷程,搭配社群網站取得之社群關係,來進行學習社群的分析,以提供學生一個社群學習的課程與社群推薦機制,協助學生選取適當的學習教材以及與其他學生產生學習上的互動與交流。
摘要(英) “Social Learning“ is one of the most nature way for people to learn. Through observation, imitation of others’ behaviors and actual activity participation and interaction with other individuals, people construct cognition, experience and memory in the series of social process, and, finally, all of them are going to be their own knowledge. In the last decade, E-learning became prosperous and brilliant with the help of Internet technologies. However, the current E-learning system mainly plays a role of learning assistance such as providing learning content or learning information, and it seldom provides channels or platforms in the learning environment for discussion and interaction. The current E-learning system can’t fully support the social learning environment. In recent years, social network sites became widespread and everyone interacted and communicated with others on the websites almost every day. This made social network sites become one of the necessary elements of nowadays people, and some other social-related researches started to study the impact brought by social networks, so did E-learning and social learning. Many researches were wondering what kinds of new features or innovations that social networks and social network sites could make up a deficiency of social learning support.
In recent years, “Open Course Ware” raised a storm in the E-learning research field. User can receive the higher education courses from the world-famous universities in the worldwide to have self-learning by simply registering an account on the websites. As traditional E-learning system breaking the time and space limitation, Open Course Ware also breaks the limitation of classroom and school. This makes the Online School or Online University become a new trend in the education, and some famous universities was even willing to provide credit certification for the Open Course Ware. However, the pure online and self-learning learning environment is working without the instruction of teacher, it was an important issue that how students receive suitable learning content in this kind of learning environment; Also, how the learning society formed in this environment can help student in the learning activities and the system design of interaction learning mechanism of social learning and peer learning are another important issue.
In our research, we integrate the E-learning system and the existing social network sites, using the power of social networks to provide an Open Course Ware environment. Moreover, we analyze the learning portfolio in the E-learning system with the social relationship acquiring from social network sites, to do the social learning analysis and provide a social learning recommendation mechanism, which can help student to choose suitable course according to their learning situation, and have interaction and discussion with other students or friends.
關鍵字(中) ★ 社群學習
★ 開放式網路課程
★ 推薦系統
關鍵字(英) ★ Social Learning
★ Open Course Ware
★ Recommendation System
論文目次 Chinese Abstract i
English Abstract iii
Acknowledgements v
Contents............................................................................................................................vi
List of Figures viii
List of Tables x
Chpater 1 Introduction 1
1.1. Research Background 1
1.2. Research Objectives 3
Chpater 2 Related Works 4
2.1 Social Learning 4
2.2 E-Learning Environment and Open Course Ware 6
2.3 Recommendation System 9
Chpater 3 Proposed System Architecture 12
3.1 Chosen Social Network Site: Facebook 13
3.2 E-learning system: MINE LMS 16
3.3 Social Learning Recommendation System 21
3.3.1. Acquiring related Information 23
3.3.2. Learning Path Similarity 23
3.3.3. Friend Recommendation 27
3.3.4. Course Recommendation 30
Chpater 4 System Implementation 39
4.1 System Implementation Environment 39
4.2 System Functionality Demonstration 41
4.2.1. Basic User Interface 41
4.2.2. Learning Management System 44
4.2.3. Social Learning Recommendation System 48
Chpater 5 Experimental Results and Analysis 55
5.1. Experiment environment 55
5.2. Experimental Results 56
5.2.1. Friend Recommendation in one specific course 56
5.2.2. Friend Recommendation in one specific category 57
5.2.3. Course Recommendation 61
5.3. Questionnaire Analysis 65
Chpater 6 Conclusion and Future Works 74
6.1. Conclusion 74
6.2. Future Works 75
References 77
Appendix 1: Experimental Result 81
Appendix 2: Questionnaire 82
Appendix 3: Interview Questions 85
參考文獻 [1] T.-S. C. Cheng-Sian Chang, Wei-Hsiang Hsu, "The Study on Integrating WebQuest with Mobile Learning for Environmental Education," Computers & Education, vol. 57, pp. 1228-1239, 2011.
[2] B. Schneider, P. Jermann, G. Zufferey, and P. Dillenbourg, "Benefits of a Tangible Interface for Collaborative Learning and Interaction," IEEE Transactions on Learning Technologies, vol. 4, pp. 222-232, 2011.
[3] M. M. Neema Moraveji, Daniel Morris, Mary Czerwinski, Nathalie Henry Riche, "ClassSearch: Facilitating the Development of Web Search Skills through Social Learning," presented at the Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2011, pp1797-1806..
[4] J. J. P. C. Rodrigues, F. M. R. Sabino, and L. Zhou, "Enhancing e-learning experience with online social networks," Communications, IET, vol. 5, pp. 1147-1154, 2011.
[5] B. Thoms, "A Dynamic Social Feedback System to Support Learning and Social Interaction in Higher Education," IEEE Transactions on Learning Technologies, vol. 4, pp. 340-352, 2011.
[6] B. F. Skinner, "The operational analysis of psychological terms," Behavioral and Brain Sciences, vol. 7, pp. 547-553, 1984.
[7] J. B. Watson, "Psychology as the behaviorist views it," Psychological Review, vol. 20, pp. 158-177, 1913.
[8] S. L. Lilienfeld, Steven J., Namy, Laura L., Woolf, Nancy J., A Framework for Everyday Thinking: Pearson, 2010.
[9] L. S. Vygotsky, "Thought and language," Bulletin of the Orton Society, vol. 14, pp. 97-98, 1964/12/01 1964.
[10] M. Resnick, "Distributed Constructionism," presented at the The International Conference of the Learning Sciences, Northwestern University, 1996.
[11] J. B. Rotter, Social Learning and Clinical Psychology: Prentice-Hall, 1954.
[12] A. Bandura, Social Learning Theory: General Learning Press, 1977.
[13] H.-J. So and T. A. Brush, "Student perceptions of collaborative learning, social presence and satisfaction in a blended learning environment: Relationships and critical factors," Computers & Education, vol. 51, pp. 318-336, 8// 2008.
[14] J. R. Evans, "Education CREATIVE THINKING AND INNOVATIVE EDUCATION IN THE DECISION SCIENCES," Decision Sciences, vol. 17, pp. 250-262, 1986.
[15] M. Alavi and D. E. Leidner, "Research Commentary: Technology-Mediated Learning—A Call for Greater Depth and Breadth of Research," Information Systems Research, vol. 12, pp. 1-10, 2001.
[16] T. F. Stafford, "Understanding motivations for Internet use in distance education," Education, IEEE Transactions on, vol. 48, pp. 301-306, 2005.
[17] A. Bates, Technology, e-Learning and Distance Education London: Routledge, 2005.
[18] L. Harasim, Hiltz, S, Teles, L, Turoff, M, Learning Networks: A Field Guide to Teaching and Learning Online Cambridge, 1995.
[19] CALCampus - About. Available: http://www.calcampus.com/about.htm
[20] T. Ellis-Christensen. What Is Virtual Education? Available: http://www.wisegeek.com/what-is-virtual-education.htm
[21] Tübingen Internet Multimedia Server. TIMMS. Available: http://timms.uni-tuebingen.de/archive/sose99.aspx
[22] China Open Resources for Education, CORE. Available: http://www.core.org.cn/
[23] T. Kobayashi, Kawafuchi, A., "Japan Open Course Ware Consortium (JOCW): A Case Study in Open Educational Resources Production and Use in Higher Education," 2008.
[24] American Council on Education Recommends 5 MOOCs for Credit. Available: http://chronicle.com/article/American-Council-on-Education/137155/
[25] Coursera. Available: https://www.coursera.org/
[26] edX. Available: https://www.edx.org/
[27] K. M. Heussner. (2012). Coursera takes step to enable students to receive college credit for it’s courses. Available: http://gigaom.com/2012/11/13/coursera-takes-step-to-enable-students-to-receive-college-credit-for-its-courses/
[28] "Possible Company Monitization Strategies, Schedule 1 of the contract between Coursera and the University of Michigan," The Chronicle of Higher Education2012.
[29] (2012). Inside the Coursera Contract: How an Upstart Company Might Profit From Free Courses. Available: http://chronicle.com/article/How-an-Upstart-Company-Might/133065/
[30] W. B. C. Nicholas J. Belkin. (1992) Information filtering and information retrieval: two sides of the same coin? Communications of the ACM 29-38.
[31] L. R. Raymond J. Mooney, "Content-Based Book Recommending Using Learning for Text Categorization," presented at the Proceedings of the SIGIR-99 Workshop on Recommender Systems: Algorithms and Evaluation, Berkeley, CA, 1999.
[32] S.-Y. Chien, "A Content-based Recommendation Mothod for Browsing Guidance in Web-based E-learning System," Computer Science and Information Engineering, Mingchuan University, 2004.
[33] B. N. M. Joseph A. Konstan, David Maltz, Jonathan L. Herlocker, Lee R. Gordon, John Riedl, High Volume, "Grouplens: Applying Collaborative Filtering to Usenet News," Communications of the ACM, vol. 40, pp. 77-87, 1997.
[34] S. D. M. Sahami, D. Heckerman, and E.Horvitz, "A bayesian approach to filtering junk E-mail," presented at the AAAI Workshop on Learning for Text Categorization, Madison, Wisconsin, 1998.
[35] G. K. Sarwar, J. Konstan, and J. Riedl, "Item-based Collaborative Filtering Recommendation Algorithms," presented at the Proceedings of the 10th international conference on World Wide Web, 2001.
[36] C. Huayue, "Personalized Learning Resources Recommendation Model Based on Transfer Learning," in International Conference on Computer Science and Electronics Engineering (ICCSEE), 2012, pp. 14-16.
[37] H. Song, P. Lu, and K. Zhao, "Improving item-based collaborative filtering recommendation system with tag," in Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on, 2011, pp. 2142-2145.
[38] P. Pin-Yu, W. Chi-Hsuan, H. Gwo-Jiun, and C. Sheng-Tzong, "The development of an Ontology-Based Adaptive Personalized Recommender System," in Electronics and Information Engineering (ICEIE), 2010 International Conference On, 2010, pp. V1-76-V1-80.
[39] R. Burke, "Hybrid Recommender Systems: Survey and Experiments," User Modeling and User-Adapted Interaction, vol. 12, pp. 331-370, 2002.
[40] J. Lu, "Personalized E-learning Material Recommender System," presented at the Proceedings of the Int. Conf. on Information Technology for Application, 2004.
[41] C.-m. C. a. H.-m. L. a. Y.-h. Chen, "Personalized E-Learning System using Item Response Theory," Computers & Education, vol. 44, pp. 237-255, 2005.
[42] M. K. Khribi, M. Jemni, and O. Nasraoui, "Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval," in Advanced Learning Technologies, 2008. ICALT ’08. Eighth IEEE International Conference on, 2008, pp. 241-245.
[43] B. V. D. B. Hans G. K. Hummel, Adriana J. Berlanga, Hendrik Drachsler, Jose Janssen, Rob Nadolski, Rob Koper, "Combining Social-based and Information-based Approaches for Personalised Recommendation on Sequencing Learning Activities," International Journal of Learning Technology, vol. 3, pp. 152-168, 2007.
[44] W. Zhi, S. Lifeng, Z. Wenwu, Y. Shiqiang, L. Hongzhi, and W. Dapeng, "Joint Social and Content Recommendation for User-Generated Videos in Online Social Network," Multimedia, IEEE Transactions on, vol. 15, pp. 698-709, 2013.
[45] L. Zhenyu, L. Jiali, K. Salamatian, and X. Gaogang, "Social Connections in User-Generated Content Video Systems: Analysis and Recommendation," Network and Service Management, IEEE Transactions on, vol. 10, pp. 70-83, 2013.
[46] P. Jonghun, L. Sang-Jin, L. Sung-Jun, K. Kwanho, C. Beom-Suk, and L. Yong-Ki, "Online Video Recommendation through Tag-Cloud Aggregation," MultiMedia, IEEE, vol. 18, pp. 78-87, 2011.
[47] A. Patidar, V. Agarwal, and K. K. Bharadwaj, "Predicting Friends and Foes in Signed Networks Using Inductive Inference and Social Balance Theory," in Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on, 2012, pp. 384-388.
[48] K. S. E. S. Pushpa, Susan Elias, Zakaria Maamar, "Referral based Expertise Search System in a Time Evolving Social Network," presented at the COMPUTE ’10 Proceedings of the Third Annual ACM Bangalore Conference 2010.
[49] G. Piatetsky-Shapiro, Discovery, Analysis, and Presentation of Strong Rules, 1991.
[50] T. I. Rakesh Agrawal, Arun Swami, "Mining Association Rules between Sets of Items in Large Databases," presented at the Proceeding SIGMOD ’93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data 1993.
指導教授 施國琛(Timothy. K. Shih) 審核日期 2013-7-15
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明