LINKING SOCIAL NETWORKS TO STUDENT LEARNING AND PERFORMANCE IN PROJECT TEAMS : THE PROMISE OF COLLABORATIVE NORMS

被引:4
|
作者
Jiang, Yuan [1 ]
Yang, Liyan [2 ]
Guo, Wenjing [2 ]
Zhang, Wei [3 ]
机构
[1] China Europe Int Business Sch, Management, Shanghai, Peoples R China
[2] Shanghai Jiao Tong Univ, Antai Coll Econ & Managementat, Shanghai, Peoples R China
[3] Sichuan Univ, Sch Publ Adm, Chengdu, Peoples R China
关键词
CONSTRUCTIVE CONTROVERSY; KNOWLEDGE TRANSFER; WORK GROUPS; MANAGEMENT; DIVERSITY; CENTRALITY; CONFLICT; ORGANIZATIONS; LEADERSHIP; INNOVATION;
D O I
10.5465/amle.2020.0103
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Integrating learning and social network literatures, we developed and tested a multistage model with collaborative norms as the linking mechanism between structural character-istics of student teams' advice-seeking networks and project-based learning outcomes. Analyses of 206 students in 47 project teams revealed that the density of team advice -seeking networks was positively related to collaborative norms. In contrast, the centrali-zation of advice-seeking networks was negatively associated with collaborative norms when the level of perceived expertness of the central member in the team was higher. Sub-sequently, collaborative norms had a positive effect on both student learning and project performance. The findings suggest that research on team-based learning effectiveness can be advanced by attending to the norming process for collaboration, through which net-work structure shapes learning and performance in teams.
引用
收藏
页码:561 / 579
页数:19
相关论文
共 50 条
  • [11] Cooperative learning through collaborative faculty-student research teams
    McWey, LM
    Henderson, TL
    Piercy, FP
    FAMILY RELATIONS, 2006, 55 (02) : 252 - 262
  • [12] Collaborative learning in VR for cross-disciplinary distributed student teams
    Forland, Ekaterina Prasolova
    McCallum, Simon
    Estrada, Jose Garcia
    2021 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS (VRW 2021), 2021, : 320 - 325
  • [13] Effective student teams for collaborative learning in an introductory university physics course
    Harlow, Jason J. B.
    Harrison, David M.
    Meyertholen, Andrew
    PHYSICAL REVIEW PHYSICS EDUCATION RESEARCH, 2016, 12 (01):
  • [14] Learning to Extract Expert Teams in Social Networks
    Chang, Chih-Chieh
    Chang, Ming-Yi
    Jhang, Jhao-Yin
    Yeh, Lo-Yao
    Shen, Chih-Ya
    IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2022, 9 (05) : 1552 - 1562
  • [15] How to improve collaborative learning with video tools in the classroom? Social vs. cognitive guidance for student teams
    Carmen Zahn
    Karsten Krauskopf
    Friedrich W. Hesse
    Roy Pea
    International Journal of Computer-Supported Collaborative Learning, 2012, 7 : 259 - 284
  • [16] How to improve collaborative learning with video tools in the classroom? Social vs. cognitive guidance for student teams
    Zahn, Carmen
    Krauskopf, Karsten
    Hesse, Friedrich W.
    Pea, Roy
    INTERNATIONAL JOURNAL OF COMPUTER-SUPPORTED COLLABORATIVE LEARNING, 2012, 7 (02) : 259 - 284
  • [17] SOCIAL NETWORKS INFLUENCE IN COLLABORATIVE LEARNING
    Saquete, E.
    Puchol, M.
    Moreda, P.
    Mazon, J. N.
    Garrigos, I.
    EDULEARN10: INTERNATIONAL CONFERENCE ON EDUCATION AND NEW LEARNING TECHNOLOGIES, 2010,
  • [18] Collaborative learning and usage of social networks
    Fernandez Ulloa, Teresa
    DIDACTICA-LENGUA Y LITERATURA, 2013, 25 : 157 - 187
  • [19] 8.2.2 On the Efficacy of Student Teams in Engineering: An Assessment of Individual Learning in Collaborative Projects
    DeFranco, Joanna F.
    Neill, Colin J.
    INCOSE International Symposium, 2014, 24 (01) : 815 - 826
  • [20] Linking Collaborative Filtering and Social Networks: Who are my Mentors?
    Brun, Armelle
    Boyer, Anne
    2010 INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2010), 2010, : 409 - 410