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    온라인 토론학습에서 사회연결망 중심도가 지식구성에 미치는 영향 = The Effect of Learners` Social Network Centralities on Knowledge Construction in Online Debating Learning

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    https://www.riss.kr/link?id=A82713062

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    This study identifies what effect and relationship in-degree centrality, out-degree centrality, closeness centrality, and betweenness centrality, individual indicators, and centralization, a group indicator of centralities, have on the learners` knowledge construction. 84 college students participated in the online debating during the spring semester in 2010 at the University in Daegu, Korea. They were then randomly assigned to one of 14 groups for this debating on the two topics for 3 weeks. This study used tools such as a Ucinet 6.347, which was a program for social network analysis, a Gunawardena, Lowe, Anderson`s interaction analysis model(1997), and finally SPSS 18.0 to analyze the resulting data. The data were analyzed by correlations, and regressions. These analytical methods have yielded descriptive statistics, Pearson correlation coefficients, and coefficients of determination. The results of this study are as follows; First, this study identified that the social network centralities such as in-degree centrality, out-degree centrality, closeness centrality, and betweenness centrality all had significant relationships with knowledge construction. Second, only out-degree centrality among them affected it. Third, centralization, an indicator of group centralities, demonstrated negative correlation with 1~4th phases except for the 5th phases of the knowledge construction model of Gunawardena et al.(1997), but they had significant affection on the 1~4th phases except for the 5th phase in the model. In conclusion, this study, combining the social network analysis with content analysis, hopes to make researchers better understand the earners` characteristics and the dynamics embedded in the process of knowledge construction, and thus help them design some strategies to activate online debating learning.
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    This study identifies what effect and relationship in-degree centrality, out-degree centrality, closeness centrality, and betweenness centrality, individual indicators, and centralization, a group indicator of centralities, have on the learners` knowl...

    This study identifies what effect and relationship in-degree centrality, out-degree centrality, closeness centrality, and betweenness centrality, individual indicators, and centralization, a group indicator of centralities, have on the learners` knowledge construction. 84 college students participated in the online debating during the spring semester in 2010 at the University in Daegu, Korea. They were then randomly assigned to one of 14 groups for this debating on the two topics for 3 weeks. This study used tools such as a Ucinet 6.347, which was a program for social network analysis, a Gunawardena, Lowe, Anderson`s interaction analysis model(1997), and finally SPSS 18.0 to analyze the resulting data. The data were analyzed by correlations, and regressions. These analytical methods have yielded descriptive statistics, Pearson correlation coefficients, and coefficients of determination. The results of this study are as follows; First, this study identified that the social network centralities such as in-degree centrality, out-degree centrality, closeness centrality, and betweenness centrality all had significant relationships with knowledge construction. Second, only out-degree centrality among them affected it. Third, centralization, an indicator of group centralities, demonstrated negative correlation with 1~4th phases except for the 5th phases of the knowledge construction model of Gunawardena et al.(1997), but they had significant affection on the 1~4th phases except for the 5th phase in the model. In conclusion, this study, combining the social network analysis with content analysis, hopes to make researchers better understand the earners` characteristics and the dynamics embedded in the process of knowledge construction, and thus help them design some strategies to activate online debating learning.

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    참고문헌 (Reference)

    1 조일현, "협동학습팀 내 사회연결망 지수가 학습 성과에 미치는 영향" 한국교육공학회 24 (24): 295-317, 2008

    2 김용학, "지식네트워크와 사회연결망" 인적자원개발원 2009

    3 김명랑, "웹기반 협동학습에서 상호의존성과 집단 유형에 대한 사회연결망 분석" 한국교육방법학회 20 (20): 155-172, 2008

    4 이지연, "웹기반 게시판을 활용한 협력학습에서의 상호작용 유형과 지식형성 과정" 한국교육공학회 21 (21): 29-58, 2005

    5 임규연, "온라인 팀 프로젝트에서 팀 리더의 상호작용 패턴 분석" 한국교육정보미디어학회 15 (15): 295-317, 2009

    6 김용학, "온라인 사회 연결망의 구조분석: 싸이월드 일촌 연결망을 중심으로" 한국정보화진흥원 13 (13): 167-185, 2006

    7 조남재, "오프라인 기반 가상공동체 구성원의 심리적 유형과 온라인 의사소통 매체에 대한 사회 연결망 분석" 한국정보화진흥원 13 (13): 20-36, 2006

    8 김용학, "사회연결망 이론" 박영사 2007

    9 손동원, "사회네트워크 분석" 경문사 2008

    10 조일현, "블렌디드 러닝 환경에서 사회 연결망 중심도와 학습자 성과 간의 상관 관계" 한국컴퓨터교육학회 10 (10): 77-87, 2007

    1 조일현, "협동학습팀 내 사회연결망 지수가 학습 성과에 미치는 영향" 한국교육공학회 24 (24): 295-317, 2008

    2 김용학, "지식네트워크와 사회연결망" 인적자원개발원 2009

    3 김명랑, "웹기반 협동학습에서 상호의존성과 집단 유형에 대한 사회연결망 분석" 한국교육방법학회 20 (20): 155-172, 2008

    4 이지연, "웹기반 게시판을 활용한 협력학습에서의 상호작용 유형과 지식형성 과정" 한국교육공학회 21 (21): 29-58, 2005

    5 임규연, "온라인 팀 프로젝트에서 팀 리더의 상호작용 패턴 분석" 한국교육정보미디어학회 15 (15): 295-317, 2009

    6 김용학, "온라인 사회 연결망의 구조분석: 싸이월드 일촌 연결망을 중심으로" 한국정보화진흥원 13 (13): 167-185, 2006

    7 조남재, "오프라인 기반 가상공동체 구성원의 심리적 유형과 온라인 의사소통 매체에 대한 사회 연결망 분석" 한국정보화진흥원 13 (13): 20-36, 2006

    8 김용학, "사회연결망 이론" 박영사 2007

    9 손동원, "사회네트워크 분석" 경문사 2008

    10 조일현, "블렌디드 러닝 환경에서 사회 연결망 중심도와 학습자 성과 간의 상관 관계" 한국컴퓨터교육학회 10 (10): 77-87, 2007

    11 Harasim, L., "글로벌 네트워크 (원서 1993년 발행)" 전예원 1997

    12 Jӓrvelӓ, S., "Web-based cases in teaching and learning-the quality of discussions and a stage of perspective taking in asynchronous communication" 10 (10): 1-22, 2002

    13 Borgatti, S. P, "Ucinet for Windows: Software for social networkanalysis"

    14 Gunawardena, C. N., "Transcript analysis of computer-mediated conferences as a tool for testing constructivist and social-constructivist learning theories" 139-145, 1998

    15 Mylläri, J., "The dynamics of an online knowledge building community: A 5-year longitudinal study" 41 (41): 365-387, 2010

    16 Cho, H., "Social networks, communication styles and learning performance in a CSCL community" 49 (49): 309-329, 2007

    17 Cho, H., "Social network analysis of information sharing networks in a CSCL community, In Proceedings of Computer Support for Collaborative Learning (CSCL) 2002 Conference, January 7-11" Lawrence Erlbaum Associates 43-50, 2002

    18 Schwab, J., "Science, curriculum, and liberal education" The University of Chicago Press 1978

    19 Knoke, D., "Prominence. In Applied network analysis:A methodological introduction" Sage 195-222, 1983

    20 Russo, T. C., "Prestige, centrality, and learning: A social network analysis of an online class" 54 (54): 254-261, 2005

    21 Lipponen, L., "Patterns of participation and discourse in elementary students' computer-supported collaborative learning" 13 : 487-509, 2003

    22 Hakkarainen, K, "Patterns of interaction in computer-supported learning: A social network analysis. In Fourth international conference of the learning sciences" Erlbaum 334-339, 2000

    23 Palonen, T., "Networked expertise and knowledge management" Department of Psychology 1999

    24 Laat, M. de., "Network and content analysis in an online community discourse" 625-637, 2002

    25 Aviv, R., "Network analysis of knowledge construction inasynchronous learning networks" 7 (7): 1-23, 2003

    26 전영국, "ICT 활용을 위한 웹자료 개발의 이론과 실제" 교우사 2005

    27 조일현, "GBS 학습 환경 하에서 상호작용 연구를 위한 사회 연결망 분석 기법의 적용" 한국컴퓨터교육학회 6 (6): 81-93, 2003

    28 Schellens, T., "Fostering knowledge construction in university students through asynchronous discussion groups" 46 : 349-370, 2006

    29 Mason, R., "Evaluation methodologies for computer conferencing applications" 105-116, 1992

    30 Mara, R. M., "Content analysis of online discussion forums: A comparative analysis of protocols" 2004

    31 Aravaja, M., "Constructing Knowledge througha role-play in a Web learning environment" 28 (28): 319-341, 2003

    32 Henri, F., "Computer conferencing content analysis. In Collaborative learning through computer conferencing" Springer-Verlag 117-136, 1992

    33 강인구, "CSCL에서 SN(Social Network)데이터의 제시가 상호작용 과정과 활동성과에 미치는 영향" 한국교육공학회 20 (20): 89-115, 2004

    34 MacDonald, J., "Assessing online collaborative learning: Process and product" 40 (40): 377-391, 2003

    35 Gunawardena, C. N., "Analysis of a global online debate and the development of an interaction analysis model for examining social construction of knowledge in computer conferencing" 17 (17): 397-431, 1997

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