Measuring Knowledge Elaboration Based on a Computer-Assisted Knowledge Map Analytical Approach to Collaborative Learning

被引:2
|
作者
Zheng, Lanqin [1 ]
Huang, Ronghuai [1 ]
Hwang, Gwo-Jen [2 ]
Yang, Kaicheng [1 ]
机构
[1] Beijing Normal Univ, Fac Educ, Sch Educ Technol, Beijing 100875, Peoples R China
[2] Natl Taiwan Univ Sci & Technol, Grad Inst Digital Learning & Educ, Taipei, Taiwan
来源
EDUCATIONAL TECHNOLOGY & SOCIETY | 2015年 / 18卷 / 01期
关键词
Knowledge elaboration; Collaborative learning; Knowledge map; Computer-assisted instructions; ARGUMENTATION;
D O I
暂无
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
The purpose of this study is to quantitatively measure the level of knowledge elaboration and explore the relationships between prior knowledge of a group, group performance, and knowledge elaboration in collaborative learning. Two experiments were conducted to investigate the level of knowledge elaboration. The collaborative learning objective in the first experiment concerned the understanding of curriculum objectives, and that of the second experiment was related to the theory and application of consumer behaviour in microeconomics. A total of 91 undergraduate students participated in the first experiment and 94 participated in the second experiment. Students were randomly divided into 30 groups of three or four in each experiment. Students' interactions were analysed based on the computer-assisted knowledge map analytical approach to measuring the level of knowledge elaboration. Empirical evidence from 60 groups demonstrates that the network structure entropy, degree distribution index, depth, and weighted path length of the activation spanning tree of the target knowledge map can be used for the precise measurement of knowledge elaboration. The results also reveal that knowledge elaboration is positively related to both prior knowledge of a group and group performance.
引用
收藏
页码:321 / 336
页数:16
相关论文
共 50 条
  • [21] Information technology and knowledge-based interactions in collaborative learning
    Pah, Iulian
    Chiribuca, Dan
    Postelnicu, Camil
    RECENT ADVANCES IN E-ACTIVITIES, INFORMATION SECURITY AND PRIVACY, 2009, : 159 - +
  • [22] Feature fusion-based collaborative learning for knowledge distillation
    Li, Yiting
    Sun, Liyuan
    Gou, Jianping
    Du, Lan
    Ou, Weihua
    INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2021, 17 (11)
  • [23] Personalized Autonomous Learning Path Planning Based on Knowledge Map
    Yang, Jin-qiu
    Bai, Jian-yu
    Wen, Shi-ting
    INTERNATIONAL CONFERENCE ON ADVANCED EDUCATION AND MANAGEMENT SCIENCE (AEMS 2017), 2017, : 224 - 227
  • [24] Multi-action-based approach for constructing knowledge map
    阎艳
    郝佳
    王国新
    宫林
    赵博
    Journal of Beijing Institute of Technology, 2015, 24 (03) : 335 - 340
  • [25] Multi-action-based approach for constructing knowledge map
    Yan, Yan
    Hao, Jia
    Wang, Guo-Xin
    Gong, Lin
    Zhao, Bo
    Journal of Beijing Institute of Technology (English Edition), 2015, 24 (03): : 335 - 340
  • [26] Epistemic activities and collaborative learning: towards an analytical model for studying knowledge construction in networked learning settings
    Zenios, Maria
    JOURNAL OF COMPUTER ASSISTED LEARNING, 2011, 27 (03) : 259 - 268
  • [27] Knowledge organization through multiple representations in a computer-supported collaborative learning environment
    Namdar, Bahadir
    Shen, Ji
    INTERACTIVE LEARNING ENVIRONMENTS, 2018, 26 (05) : 638 - 653
  • [28] Identifying Knowledge-building Phases in Computer-supported Collaborative Learning: A Review
    Said, Tamer
    Shawky, Doaa
    Badawi, Ashraf
    PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON INTERACTIVE COLLABORATIVE LEARNING (ICL), 2015, : 608 - 614
  • [29] Motivation in a computer-supported collaborative learning scenario and its impact on learning activities and knowledge acquisition
    Schoor, Cornelia
    Bannert, Maria
    LEARNING AND INSTRUCTION, 2011, 21 (04) : 560 - 573
  • [30] Research on Learning Resource Recommendation Based on Knowledge Graph and Collaborative Filtering
    Niu, Yanmin
    Lin, Ran
    Xue, Han
    APPLIED SCIENCES-BASEL, 2023, 13 (19):