The impacts of the comprehensive learning analytics approach on learning performance in online collaborative learning

被引:0
|
作者
Lanqin Zheng
Yunchao Kinshuk
Miaolang Fan
机构
[1] Beijing Normal University,School of Educational Technology, Faculty of Education
[2] University of North Texas,undefined
来源
关键词
Learning analytics; Online collaborative learning; Collaborative knowledge building; Coregulation; Learning engagement; Social interaction;
D O I
暂无
中图分类号
学科分类号
摘要
Online collaborative learning has been an effective pedagogy in the field of education. However, productive collaborative learning cannot occur spontaneously. Learners often have difficulties in collaborative knowledge building, group performance, coregulated behaviors, learning engagement, and social interaction. To promote productive collaborative learning, this study aims to propose and validate a comprehensive learning analytics approach in an online collaborative learning context. The comprehensive learning analytics can automatically construct knowledge graphs, analyze metacognitive learning engagement and social interaction and provide personalized feedback. A total of 90 college students participated in this study, and they were assigned to the experimental group and control group. The students in the experimental group conducted online collaborative learning with the comprehensive learning analytics approach, while the students in the control group conducted traditional online collaborative learning without any specific approach. The results indicated that the comprehensive learning analytics approach significantly improved collaborative knowledge building, group performance, coregulated behaviors, metacognitive learning engagement, and social interaction compared with traditional online collaborative learning. In this paper, the results of the study together with the implications are discussed.
引用
收藏
页码:16863 / 16886
页数:23
相关论文
共 50 条
  • [1] The impacts of the comprehensive learning analytics approach on learning performance in online collaborative learning
    Zheng, Lanqin
    Kinshuk
    Fan, Yunchao
    Long, Miaolang
    [J]. EDUCATION AND INFORMATION TECHNOLOGIES, 2023, 28 (12) : 16863 - 16886
  • [2] A COMPREHENSIVE APPROACH TO LEARNING ANALYTICS
    Gaftandzhieva, S.
    Doneva, R.
    [J]. 12TH INTERNATIONAL CONFERENCE OF EDUCATION, RESEARCH AND INNOVATION (ICERI 2019), 2019, : 2634 - 2643
  • [3] Student learning performance in online collaborative learning
    Peggy M. L. Ng
    Jason K. Y. Chan
    Kam Kong Lit
    [J]. Education and Information Technologies, 2022, 27 : 8129 - 8145
  • [4] Student learning performance in online collaborative learning
    Ng, Peggy M. L.
    Chan, Jason K. Y.
    Lit, Kam Kong
    [J]. EDUCATION AND INFORMATION TECHNOLOGIES, 2022, 27 (06) : 8129 - 8145
  • [5] A Learning Analytics Study of the Effect of Group Size on Social Dynamics and Performance in Online Collaborative Learning
    Saqr, Mohammed
    Nouri, Jalal
    Jormanainen, Ilkka
    [J]. TRANSFORMING LEARNING WITH MEANINGFUL TECHNOLOGIES, EC-TEL 2019, 2019, 11722 : 466 - 479
  • [6] Learning analytics for learning design in online distance learning
    Holmes, Wayne
    Quan Nguyen
    Zhang, Jingjing
    Mavrikis, Manolis
    Rienties, Bart
    [J]. DISTANCE EDUCATION, 2019, 40 (03) : 309 - 329
  • [7] Learning Analytics Measuring Impacts on Organisational Performance
    Maria José Sousa
    Álvaro Rocha
    [J]. Journal of Grid Computing, 2020, 18 : 563 - 571
  • [8] Learning Analytics Measuring Impacts on Organisational Performance
    Sousa, Maria Jose
    Rocha, Alvaro
    [J]. JOURNAL OF GRID COMPUTING, 2020, 18 (03) : 563 - 571
  • [9] The impacts of cognitive learning styles on the use of online learning and collaborative writing environments
    Ma, Will W. K.
    Sun, Kirindi
    Ma, Jamie
    [J]. INTERNATIONAL JOURNAL OF INNOVATION AND LEARNING, 2014, 16 (01) : 97 - 111
  • [10] Integrating Learning Analytics and Collaborative Learning for Improving Student's Academic Performance
    Rafique, Adnan
    Khan, Muhammad Salman
    Jamal, Muhammad Hasan
    Tasadduq, Mamoona
    Rustam, Furqan
    Lee, Ernesto
    Washington, Patrick Bernard
    Ashraf, Imran
    [J]. IEEE ACCESS, 2021, 9 : 167812 - 167826