Factors that impact social networking in online self-regulated learning activities

被引:3
作者
Yu, Xiaohua [1 ]
Wang, Charles Xiaoxue [2 ]
Spector, J. Michael [3 ]
机构
[1] East China Normal Univ, Fac Educ, Dept Educ Informat Technol, 3663 North Zhongshan Rd, Shanghai, Peoples R China
[2] Florida Gulf Coast Univ, Coll Educ, 10501 FGCU Blvd South, Ft Myers, FL 33965 USA
[3] Univ North Texas, Coll Informat, Dept Learning Technol, 3940 N Elm St,Suite G 150, Denton, TX 76207 USA
来源
ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT | 2020年 / 68卷 / 06期
关键词
Follow links; Learning analytics; Learning engagement; Online learning; Resource platform; Self-regulated learning; Social networking; HIGHER-EDUCATION; FACEBOOK; SITES; PERCEPTIONS; EFFICACY; ACHIEVEMENT; FEEDBACK; FRIENDS;
D O I
10.1007/s11423-020-09843-9
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Among the literature on self-regulated learning and social networking, the studies, which explore the impact of social networks on learning regarding connection sizes and relationship-establishing factors, are rarely seen in the context of social networking among strangers. This descriptive study addresses the gap by exploring data from 468 Chinese junior high school graduates in an online learning resource platform with an integrated social network. The data is digitally generated when the graduates engaged in online self-regulated learning activities for an average of 36 days without any facilitations. The data analysis explores the connection sizes and types of follow links, types of self-regulated learners, and their relationship with lesson completion. The study reveals that social networks trigger different levels of learning engagement. Specifically, the graduates with bidirectional follow links and the optimal connection size of five complete more lessons than other graduates. The study also finds that academic factors (similar learning goals and achievement gaps) are more important than social factors (common identity) in establishing social connections to support self-regulated learning activities. These findings have direct implications for the design of social networking that facilitates self-regulated learning, and enhances students' self-regulated learning efficacy in online learning environments.
引用
收藏
页码:3077 / 3095
页数:19
相关论文
共 53 条
  • [1] Social networking sites and cognitive abilities: Do they make you smarter?
    Alloway, Tracy Packiam
    Horton, John
    Alloway, Ross G.
    Dawson, Clare
    [J]. COMPUTERS & EDUCATION, 2013, 63 : 10 - 16
  • [2] The development of competence-related and motivational beliefs: An investigation of similarity and influence among friends
    Altermatt, ER
    Pomerantz, EM
    [J]. JOURNAL OF EDUCATIONAL PSYCHOLOGY, 2003, 95 (01) : 111 - 123
  • [3] [Anonymous], 1989, SELF REGULATED LEARN
  • [4] [Anonymous], 2014, J Learn Analytics, DOI [10.18608/jla.2014.12.3, DOI 10.1145/2460296.2460312, DOI 10.18608/JLA.2014.12.3]
  • [5] A review of research on Facebook as an educational environment
    Aydin, Selami
    [J]. ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT, 2012, 60 (06): : 1093 - 1106
  • [6] The role of self-efficacy, task value, and achievement goals in predicting learning approaches and mathematics achievement
    Azar, Hemin Khezri
    Lavasani, Masoud G.
    Malahmadi, Ehsan
    Amani, Javad
    [J]. WCPCG 2010, 2010, 5 : 942 - 947
  • [7] Bakshy E., 2011, P 4 ACM INT C WEB SE, DOI [https://doi.org/10.1145/1935826.1935845, DOI 10.1145/1935826.1935845]
  • [8] SELF-EFFICACY - TOWARD A UNIFYING THEORY OF BEHAVIORAL CHANGE
    BANDURA, A
    [J]. PSYCHOLOGICAL REVIEW, 1977, 84 (02) : 191 - 215
  • [9] Bandura A, 1986, SOCIAL FDN THOUGHT A, DOI DOI 10.5465/AMR.1987.4306538
  • [10] Process mining techniques for analysing patterns and strategies in students' self-regulated learning
    Bannert, Maria
    Reimann, Peter
    Sonnenberg, Christoph
    [J]. METACOGNITION AND LEARNING, 2014, 9 (02) : 161 - 185