政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/119338

政大典藏 > College of Liberal Arts > Graduate Institute of Library, Information and Archival Studies > Theses > Item 140.119/119338

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/119338

Title:	發展語義分析網路即時回饋系統促進線上討論成效 Developing Semantic Network Instant Feedback System to Facilitate Online Discussion Performance
Authors:	黃雅翎 Huang, Ya-Ling
Contributors:	陳志銘 Chen, Chin-Ming 黃雅翎 Huang, Ya-Ling
Keywords:	線上討論社會網絡社會性科學議題社會性科學議題推理電腦中介溝通認知風格學習成效科技接受度 Online discussion Social network Socio-scientific issues Socio-scientific reasoning Computer-mediated communication Cognitive style Learning effectiveness Technology acceptance
Date:	2018
Issue Date:	2018-08-13 12:36:03 (UTC+8)
Abstract:	討論對於學習者是一個萌生對議題想法必經的過程，透過討論可提升對於議題的瞭解，過程中可針對資訊進行篩選、消化以及吸收，有效的討論有助於提升學習成效。為求即時與便利，透過網路討論已是無可避免的趨勢。因此，本研究設計「語義分析網路即時回饋系統（Semantic Network Instant Feedback System，簡稱SNIFS）」，希望透過呈現學習者討論內容中的詞彙語意網絡，輔助學習者掌握問題討論方向，進而有效提升網路學習成效。本研究採用準實驗研究，隨機選取台北市某高中二年級兩班共64名學生為研究對象，進行「核能發電與燃煤發電選擇」主題之線上討論。其中採用「SNIFS輔助討論區」輔以線上討論的實驗組學生32名，僅採用一般傳統線上討論區輔以線上討論的控制組學生32名，探討兩組學習者在學習成效與科技接受度上是否具有顯著差異。此外，也以先備知識、電腦中介溝通（Computer-Mediated Communication，簡稱CMC）能力以及認知風格作為背景變項，探討兩組具三種不同背景變項的學習者，在學習成效及科技接受度上是否具有顯著差異。研究結果發現，相較於使用一般傳統線上討論區，採用「SNIFS輔助討論區」對於低先備知識以及高CMC能力學習者的學習成效具有顯著的助益。SNIFS能夠幫助低先備知識的學習者產生更多的觀點，也能夠幫助高CMC能力學習者提高討論的複雜度，使其對討論議題有更深入地認識。而在科技接受度上，實驗組與控制組的分數普遍偏低，顯示兩組學習者對於系統的科技接受度都不算高。在兩組科技接受度皆不高的情況下，整體控制組學習者或是文字型學習者在科技接受度及認知易用性上顯著優於實驗組。此外，本研究之質性資料分析顯示，造成控制組學習者科技接受度優於實驗組的可能原因，為學習者認為本研究所採用之討論區不完全符合需求，而實驗組除了討論區外，還需要使用SNIFS，因此增添了系統的複雜性，進而影響到實驗組學習者使用SNIFS系統進行討論的流暢度。最後基於研究結果，本研究提出SNIFS以及一般線上討論區設計上的改進建議，以及未來可以繼續發展的研究方向。整體而言，本研究發展的SNIFS系統有助於發展出結合線上討論區及討論詞彙語意視覺化之創新線上討論工具，對於促進網路學習之線上討論成效具有貢獻。 Discussion is the process for a learner coming up with ideas about an issue. Discussion could enhance the understanding of issues and selecting, digesting, and absorbing information in the process. Effective discussion could enhance learning effectiveness. For the immediacy and convenience, online discussion has become an inevitable trend. The “Semantic Network Instant Feedback System (SNIFS)” is therefore designed in this study, expecting to present the semantic network of words used in learners’ discussion contents, assist learners in grasping the question discussion direction, and further effectively enhance online learning effectiveness. With quasi-experimental research, a total of 64 Grade 11 students from two classes of a senior high school in Taipei City are randomly selected as the research subjects for the online discussion of “options of nuclear power generation and coal-fired power generation”. “SNIFS assisted discussion” is applied to 32 students in the experimental group, and general online discussion is used for another 32 students in the control group. The learning effectiveness and technology acceptance of the learners in two groups are discussed the differences. Furthermore, prior knowledge, computer-mediated communication (CMC) ability, and cognitive styles are used as the background variables to discuss the effects on learning effectiveness and technology acceptance. The research results discover that “SNIFS assisted discussion”, compared to general online discussion, shows significant benefits on the learning effectiveness of learners with low prior knowledge and high CMC ability. SNIFS could help learners with low prior knowledge generate more points of view as well as assist those with high CMC ability in enhancing the discussion complexity to have deeper understanding of the discussed issue. In terms of technology acceptance, both the experimental group and the control group present lower scores, revealing low technology acceptance of learners in both groups. In this case, learners in the control group or verbalizers remarkably outperform those in the experiment group on technology acceptance and perceived ease of use. Furthermore, the qualitative data analysis in this study reveals that learners in the control group outperforming those in the experimental group on technology acceptance possibly because learners consider the applied discussion not completely conforming to the demands. The experimental group, on the other hand, has to use SNIFS beyond discussion that increases the system complexity and further affects the fluency in the discussion with the SNIFS system. Based on the research result, suggestions for improving the design of SNIFS and general online discussion and future research directions are proposed in this study. Overall speaking, the SNIFS system developed in this study could help develop the innovative online discussion tool combining online discussion and semantic visualization of discussed words to contribute to the online discussion learning effectiveness.
Reference:	周君倚、陸洛（2014）。以科技接受模式探討數位學習系統使用態度－以成長需求為調節變項。資訊管理學報，21(1)，83-106。林樹聲（2003）。重視自然與生活科技學習領域中科技爭議議題的融入與探討。載於林生傳（主編），國民中小學九年一貫課程理論基礎（一）（453-465 頁）。臺北市：教育部。胡幼慧（1996）。質性研究：理論、方法及本土女性研究實例。臺北市：巨流。陳其芬（2005）。非同步線上討論應用於英語專業課程之互動模式與言談行為探討（NSC94-2411-H-327-005)。高雄市：國立高雄第一科技大學應用英語研究所。檢自國立高雄科技大學第一校區機構典藏：http://repository.nkfust.edu.tw/ir/retrieve/18348/NSC94-2411-H327-005.pdf Althaus, S. L. (1997). Computer-Mediated Communication in the University Classroom: An Experiment with On-line Discussions. Communication Education, 46(3), 158–174. doi:10.1080/03634529709379088 Andresen, M. A. (2009). Asynchronous discussion forums: success factors, outcomes, assessments, and limitations. Educational Technology & Society, 12(1), 249–257. Arabie, P., Carroll, J. D., & DeSarbo, W. S. (1987). Three-way scaling and clustering. Newbury Park, CA: Sage. Aviv, R., Erlich, Z., Ravid, G., & Geva, A. (2003). Network analysis of knowledge construction in asynchronous learning networks. Journal of Asynchronous Learning Networks, 7(3), 1–23. Barnes, J. A. (1954). Class and Committees in a Norwegian Island Parish. Human Relations, 7(1), 39–58. doi:10.1177/001872675400700102 Bassett, D. S., & Bullmore, E. T. (2016). Small-World Brain Networks Revisited. The Neuroscientist. doi:10.1177/1073858416667720 Borgatti, S.P., Everett, M.G., & Freeman, L.C. (2002). UCINET for Windows: Software for social network analysis. Harvard,MA: Analytic Technologies. Branon, R., & Essex, C. (2001). Synchronous and asynchronous communication tools in distance education. TechTrends, 45(1), 36–36. doi:10.1007/BF02763377 Camp, G. (1996). Problem-Based Learning: A Paradigm Shift or a Passing Fad? Medical Education Online, 1(1). doi:10.3402/meo.v1i.4282 Chen, G. W., & Chiu, M. M. (2006). Online discussion processes: Effects of earlier messages’ evaluations, knowledge content, social cues and personal information on later messages. Computers & Education. doi:10.1016/j.compedu.2006.07.007 Chen, S.-J., & Caropreso, E. J. (2004). Influence of personality on online discussion. Journal of Interactive Online Learning, 3(2), 1-17. Childers, T. L., Houston, M. J., & Heckler, S. E. (1985). Measurement of Individual Differences in Visual versus Verbal Information Processing. Journal of Consumer Research, 12(2), 125–134. doi:10.1086/208501 Cole, J., & Foster, H. (2007). Using Moodle: Teaching with the popular open source course management system. (2nd ed.). Sebastopol, CA: O’Reilly. Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: theory and results. (Doctoral dissertation, Massachusetts Institute of Technology). Retrived from http://hdl.handle.net/1721.1/15192 Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1003. doi: 10.1287/mnsc.35.8.982 Dennen, V. P. (2005). From message posting to learning dialogues: Factors affecting learner participation in asynchronous discussion. Distance Education, 26(1), 127–148. doi:10.1080/01587910500081376 Dourish, P. & Chalmers, M. (1994). Running out of Space: Models of Information Navigation. Proceedings of HCI `94, Glasgow, Scotland: ACM Press. Watts, D. J.& Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393, 440–442. doi:10.1038/30918 Duncan, M. J., Smith, M., & Cook, K. (2013). Implementing online problem based learning (PBL) in postgraduates new to both online learning and PBL: An example from strength and conditioning. Journal of Hospitality, Leisure, Sport and Tourism Education, Journal of Hospitality, Leisure, Sports and Tourism Education, 12(1), 79–84. doi:10.1016/j.jhlste.2012.11.004 Erlin, B., Yusof, N., & Rahman, A. A. (2008). Integrating content analysis and social network analysis for analyzing asynchronous discussion forum. In International Symposium on Information Technology 2008 (Vol. 3, pp.1-8). doi:10.1109/ITSIM.2008.4631996 Erlin, B., Yusof, N., & Rahman, A. A. (2009). Students’ Interactions in Online Asynchronous Discussion Forum: A Social Network Analysis. In 2009 International Conference on Education Technology and Computer (pp. 25-29). Singapore, Singapore: IEEE. doi: 10.1109/ICETC.2009.48 Farzan, R. and Brusilovsky, P. (2005). Social navigation support in E-Learning: What are real footprints. In Proceedings of IJCAI(Vol. 5, pp.49-56). Freeman, L. (2004). The development of social network analysis. A Study in the Sociology of Science. New York, NY: Empirical Press. Gao, F., Zhang, T., & Franklin, T. (2013). Designing asynchronous online discussion environments: Recent progress and possible future directions. British Journal of Educational Technology, 44(3), 469–483. doi:10.1111/j.1467-8535.2012.01330.x Gerosa, M. A., Filippo, D., Pimentel, M., Fuks, H., & Lucena, C. J. P. (2010). Is the unfolding of the group discussion off-pattern? Improving coordination support in educational forums using mobile devices. Computers & Education, 54(2), 528–544. doi:10.1016/j.compedu.2009.09.004 Hara, N., Bonk, C. J., & Angeli, C. (2000). Content Analysis of Online Discussion in an Applied Educational Psychology Course. Instructional Science, 28(2), 115–52. doi:10.1023/A:1003764722829 Hew, K. F., & Cheung, W. S. (2010). Possible Factors Influencing Asian Students’ Degree of Participation in Peer-Facilitated Online Discussion Forums: A Case Study. Asia Pacific Journal of Education, 30(1), 85–104. doi:10.1080/02188790903503619 Hew, K. F., & Cheung, W. S. (2011). Higher-Level Knowledge Construction in Asynchronous Online Discussions: An Analysis of Group Size, Duration of Online Discussion, and Student Facilitation Techniques. Instructional Science: An International Journal of the Learning Sciences, 39(3), 303–319. doi:10.1007/s11251-010-9129-2 Hew, K. F., Cheung, W. S., & Ng, C. S. L. (2010). Student Contribution in Asynchronous Online Discussion: A Review of the Research and Empirical Exploration. Instructional Science: An International Journal of the Learning Sciences, 38(6), 571–606. doi:10.1007/s11251-008-9087-0 Hung, M.-L., & Chou, C. (2014). The Development, Validity, and Reliability of Communication Satisfaction in an Online Asynchronous Discussion Scale. The Asia-Pacific Education Researcher, 23(2), 165–177. doi:10.1007/s40299-013-0094-9 Hwang, G.-J., Yang, L.-H., & Wang, S.-Y. (2013). A concept map-embedded educational computer game for improving students’ learning performance in natural science courses. Computers & Education, 69, 121–130. doi:10.1016/j.compedu.2013.07.008 Kayler, M., & Weller, K. (2008). Pedagogy, Self-Assessment, and Online Discussion Groups. Journal of Educational Technology & Society, 10(1), 136–147. Klisc, C., Mcgill, T., & Hobbs, V. (2017). Use of a Post-Asynchronous Online Discussion Assessment to Enhance Student Critical Thinking. Australasian Journal of Educational Technology, 33(5), 63–76. doi:10.14742/ajet.3030 Kozhevnikov, M., Hegarty, M., & Mayer, R. E. (2002). Revising the Visualizer-Verbalizer Dimension: Evidence for Two Types of Visualizers. Cognition and Instruction, 20(1), 47–77. doi:10.1207/S1532690XCI2001_3 Lim, K. Y., Heo, H. O., & Kim,Y. S. (2009). Team Leaders" Interaction Patterns in Online Team Project. Korea Association Of Educational Information & Broadcasting, 15(4), 295-317. Laat, M., Lally, V., Lipponen, L., & Simons, R.-J. (2007). Investigating patterns of interaction in networked learning and computer-supported collaborative learning: A role for Social Network Analysis. International Journal of Computer-Supported Collaborative Learning, 2(1), 87–103. doi:10.1007/s11412-007-9006-4 Lan, Y.-F., Tsai, P.-W., Yang, S.-H., & Hung, C.-L. (2012). Comparing the social knowledge construction behavioral patterns of problem-based online asynchronous discussion in e/m-learning environments. Computers & Education, 59(4), 1122–1135. doi:10.1016/j.compedu.2012.05.004 Latapy, M., Magnien, C., & Vecchio, N. D. (2008). Basic notions for the analysis of large two-mode networks. Social Networks, 30(1), 31–48. doi:10.1016/j.socnet.2007.04.006 Leflay, K., & Groves, M. (2013). Using online forums for encouraging higher order thinking and ‘deep’ learning in an undergraduate Sports Sociology module. Journal of Hospitality, Leisure, Sport & Tourism Education, 13, 226–232. doi:10.1016/j.jhlste.2012.06.001 Levin, H. M., & And Others. (1987). Cost-Effectiveness of Computer-Assisted Instruction. Evaluation Review, 11(1), 50–72. doi:10.1177/0193841X8701100103 Liccardi, I., Ounnas, A., Pau, R., Massey, E., Kinnunen, P., Lewthwaite, S., … Sarkar, C. (2007). The role of social networks in students’ learning experiences. ACM Sigcse Bulletin 39(4), 224-237. doi:10.1145/1345375.1345442 Lim, S. C. R., Cheung, W. S., & Hew, K. F. (2011). Critical Thinking in Asynchronous Online Discussion: An Investigation of Student Facilitation Techniques. New Horizons in Education, 59(1), 52–65. Liu, O. L. (2012). Student Evaluation of Instruction: In the New Paradigm of Distance Education. Research in Higher Education, 53(4), 471–486. doi:10.1007/s11162-011-9236-1 Lo, H.-C. (2009). Utilizing Computer-Mediated Communication Tools for Problem-Based Learning. Educational Technology & Society, 12(1), 205–213. Majid, S., Yang, P., Lei, H., & Haoran, G. (2014). Knowledge Sharing by Students: Preference for Online Discussion Board vs Face-to-Face Class Participation. In International Conference on Asian Digital Libraries (pp. 149–159). Springer, Cham. doi:10.1007/978-3-319-12823-8_16 Marei, H. F., & Al‐Khalifa, K. S. (2016). Pattern of online communication in teaching a blended oral surgery course. European Journal of Dental Education, 20(4), 213–217. doi:10.1111/eje.12163 Marin, A., & Wellman, B. (2011). Social Network Analysis: An Introduction. In The SAGE Handbook of Social Network Analysis (pp. 11–25). Los Angeles, CA: SAGE. Mayer, R. E., & Massa, L. J. (2003). Three Facets of Visual and Verbal Learners: Cognitive Ability, Cognitive Style, and Learning Preference. Journal of Educational Psychology, 95(4), 833–846. doi:10.1037/0022-0663.95.4.833 Meyer, K. A. (2003). Face-to-face versus threaded discussions: The role of time and higher-order thinking. Journal of Asynchronous Learning Networks, 7(3), 55–65. Moran, A. (1991). What Can Learning Styles Research Learn from Cognitive Psychology? Educational Psychology: An International Journal of Experimental Educational Psychology, 11, 239–245. Morris, L. V., Finnegan, C., & Wu, S.-S. (2005). Tracking student behavior, persistence, and achievement in online courses. The Internet and Higher Education, 8(3), 221–231. doi:10.1016/j.iheduc.2005.06.009 Ng, C. S. L., Cheung, W. S., & Hew, K. F. (2012). Interaction in Asynchronous Discussion Forums: Peer Facilitation Techniques. Journal of Computer Assisted Learning, 28(3), 280–294. doi:10.1111/j.1365-2729.2011.00454.x Ouyang, F., & Scharber, C. (2017). The influences of an experienced instructor’s discussion design and facilitation on an online learning community development: A social network analysis study. The Internet and Higher Education, 35, 34–47. doi:10.1016/j.iheduc.2017.07.002 Palazuelos, C., García-Saiz, D., & Zorrilla, M. (2013). Social Network Analysis and Data Mining: An Application to the E-learning Context. In C. Badica, N. T. Nguyen, M. Brezovan (Eds.), Proceedings of the 5th International Conference on Computational Collective Intelligence (pp. 651-660). Craiova, Romania. doi:10.1007/978-3-642-40495-5_65 Parks‐Stamm, E. J., Zafonte, M., & Palenque, S. M. (2017). The effects of instructor participation and class size on student participation in an online class discussion forum. British Journal of Educational Technology, 48(6), 1250–1259. doi:10.1111/bjet.12512 Willging, P. A . (2005). Using Social Network Analysis Techniques to Examine Online Interactions.US-China Education Review, 2(9), 46-56. Peterson, A. T., & Roseth, C. J. (2016). Effects of four CSCL strategies for enhancing online discussion forums: Social interdependence, summarizing, scripts, and synchronicity. International Journal of Educational Research, 76, 147–161. doi:10.1016/j.ijer.2015.04.009 Poscente, K. R., & Fahy, P. J. (2003). Investigating Triggers in CMC Text Transcripts. The International Review of Research in Open and Distributed Learning, 4(2). doi:10.19173/irrodl.v4i2.141 Russo, T. C., & Koesten, J. (2005). Prestige, Centrality, and Learning: A Social Network Analysis of an Online Class. Communication Education, 54(3), 254–261. doi:10.1080/03634520500356394 Sadler, T. D., Barab, S. A., & Scott, B. (2007). What do Students Gain by Engaging in Socioscientific Inquiry? Research in Science Education, 37(4), 371–391. doi:10.1007/s11165-006-9030-9 Scott, J. (2000). Social network analysis: a handbook (2nd ed..). Thousand Oaks, CA: SAGE. Scott, J. (2017). Social Network Analysis. London: SAGE. Scott, J., & Carrington, P. J. (2011). The SAGE handbook of social network analysis. Los Angeles, CA: SAGE. Skylar, A. A. (2009). A Comparison of Asynchronous Online Text-Based Lectures and Synchronous Interactive Web Conferencing Lectures. Issues in Teacher Education, 18(2), 69–84. Smith, D. G. (1977). College classroom interactions and critical thinking. Journal of Educational Psychology, 69(2), 180–190. doi:10.1037/0022-0663.69.2.180 So, H.-J. (2009). When Groups Decide to Use Asynchronous Online Discussions: Collaborative Learning and Social Presence under a Voluntary Participation Structure. Journal of Computer Assisted Learning, 25(2), 143–160. doi:10.1111/j.1365-2729.2008.00293.x Spitzberg, B. H. (2006). Preliminary Development of a Model and Measure of Computer-Mediated Communication (CMC) Competence. Journal of Computer-Mediated Communication, 11(2), 629–666. doi:10.1111/j.1083-6101.2006.00030.x Sundar, S. S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In M. J. Metzger & A. J. Flanagin (Eds.), Digital media, youth, and credibility (pp. 72-100). Cambridge, MA: The MIT Press. Tagg, A., & Dickinson, J. (1995). Tutor messaging and its effectiveness in encouraging student participation on computer conferences. International Journal of E-Learning & Distance Education, 10(2), 33–55. Thoms, B., & Eryilmaz, E. (2014). How media choice affects learner interactions in distance learning classes. Computers & Education, 75, 112–126. doi:10.1016/j.compedu.2014.02.002 Tiene, D. (2000). Online Discussions: A Survey of Advantages and Disadvantages Compared to Face-to-Face Discussions. Journal of Educational Multimedia and Hypermedia, 9(4), 369–382. Vercellone-Smith, P., Jablokow, K., & Friedel, C. (2012). Characterizing communication networks in a web-based classroom: Cognitive styles and linguistic behavior of self-organizing groups in online discussions. Computers & Education, 59(2), 222–235. doi:10.1016/j.compedu.2012.01.006 Vrasidas, C., & Mcisaac, M. S. (1999). Factors Influencing Interaction in an Online Course. American Journal of Distance Education, 13(3), 22–36. doi: 10.1080/08923649909527033 Wasserman, S., & Faust, K. (1994). Social Network Analysis: Methods and Applications. England: Cambridge University Press. Wellman, B. (1992). Which types of ties and networks provide what kinds of social support. In Advances in group processes (Vol. 9, pp. 207–235). JAI Press. Willis, S. C., Jones, A., Bundy, C., Burdett, K., Whitehouse, C. R., & O’Neill, P. A. (2002). Small-group work and assessment in a PBL curriculum: a qualitative and quantitative evaluation of student perceptions of the process of working in small groups and its assessment. Medical Teacher, 24(5), 495–501. doi:10.1080/0142159021000012531 Witkin, H. A., Moore, C. A., Goodenough, D., & Cox, P. W. (1977). Field-Dependent and Field-Independent Cognitive Styles and Their Educational Implications. Review of Educational Research, 47(1), 1–64. doi:10.3102/00346543047001001 Xie, K., Miller, N. C., & Allison, J. R. (2013). Toward a Social Conflict Evolution Model: Examining the Adverse Power of Conflictual Social Interaction in Online Learning. Computers & Education, 63, 404–415. doi:10.1016/j.compedu.2013.01.003 Xie, K., Yu, C., & Bradshaw, A. C. (2014). Impacts of role assignment and participation in asynchronous discussions in college-level online classes. The Internet and Higher Education, 20, 10–19. doi:10.1016/j.iheduc.2013.09.003 Zeidler, D., & Nichols, B. (2009). Socioscientific issues: Theory and practice. Journal of Elementary Science Education, 21(2), 49–58. doi:10.1007/BF03173684 Zhu, E. (2006). Interaction and Cognitive Engagement: An Analysis of Four Asynchronous Online Discussions. Instructional Science: An International Journal of Learning and Cognition, 34(6), 451–480. doi:10.1007/s11251-006-0004-0
Description:	碩士國立政治大學圖書資訊與檔案學研究所 105155013
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G1051550131
Data Type:	thesis
DOI:	10.6814/THE.NCCU.LIAS.013.2018.A01
Appears in Collections:	[Graduate Institute of Library, Information and Archival Studies] Theses

Files in This Item:

File	Size	Format
013101.pdf	6607Kb	Adobe PDF2	18	View/Open

社群 sharing

Loading...