Effects of Online Learning on College Students in Eastern China: A Structural Equation Model

被引:9
|
作者
Zhu, Junqi [1 ]
Zhao, Haixia [2 ]
Wang, Xue [1 ]
Yang, Li [1 ]
Qin, Zhiyuan [1 ]
Geng, Jichao [1 ]
机构
[1] Anhui Univ Sci & Technol, Sch Econ & Management, Huainan, Peoples R China
[2] Anhui Univ Sci & Technol, Sch Earth & Environm, Huainan, Peoples R China
关键词
learning behavior; learning cognition; learning effect; learning environment; online learning; EDUCATION; COURSES; CHALLENGES; IMPACT; MOOC;
D O I
10.3389/fpubh.2022.853928
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
With the spread of COVID-19 worldwide, online education is rapidly catching on, even in some underdeveloped countries and regions. Based on Bandura's ternary learning theory and literature review, this paper takes online learning of college students as the research object and conducts an empirical survey on 6,000 college students in East China. Based on literature review and factor analysis and structural equation model, this paper discusses the relationship among learning cognition, learning behavior, and learning environment in online learning of college students. The learning behavior includes interactive communication, self-discipline mechanism, classroom learning, and study after class. The learning environment includes teaching ability, knowledge system, platform support, process control, and result evaluation; learning cognition includes learning motivation, information perception, and adaptability. It is found that the learning environment has a significant positive impact on learning behavior, and learning cognition has a significant positive impact on learning behavior. It is uncertain whether the learning environment significantly impacts learning cognition. At the learning environment level, the teaching ability (0.59) has the most significant impact on the learning environment, followed by result evaluation (0.42), platform support (0.40), process control (0.33), and knowledge system (0.13). In terms of the influence on learning behavior, classroom learning has the most significant impact (0.79), followed by self-discipline mechanism (0.65), study after class (0.54), and interactive communication (0.44). In terms of learning cognition, information perception (0.62) has the most significant influence, followed by learning motivation (0.50) and adaptability (0.41). This paper suggests strengthening the construction of platforms and digital resources to create a more competitive learning environment. Improve process management and personalized online services, constantly stimulate students' enthusiasm for independent online learning, and cultivate students' online independent learning ability to promote the sustainable and healthy development of online education.
引用
收藏
页数:13
相关论文
共 50 条
  • [21] An Analysis of College Students' Trust for Taobao Sellers Based on the PLS Structural Equation Model
    Yu Zhuo-xi
    Teng Fei
    STATISTIC APPLICATION IN MODERN SOCIETY, 2015, : 336 - 344
  • [22] Food Safety Attitudes in College Students: A Structural Equation Modeling Analysis of a Conceptual Model
    Booth, Rachelle
    Hernandez, Magaly
    Baker, Erica L.
    Grajales, Tevni
    Pribis, Peter
    NUTRIENTS, 2013, 5 (02): : 328 - 339
  • [23] Positive effects of online games on the growth of college students: A qualitative study from China
    Li, Feiyue
    Zhang, Di
    Wu, Suowei
    Zhou, Rui
    Dong, Chaoqun
    Zhang, Jingjing
    FRONTIERS IN PSYCHOLOGY, 2023, 14
  • [24] Factors Influencing College Students' Learning Intention to Online Teaching Videos During the Pandemic in China
    Hao, Yinhua
    Zeng, Xiangmin
    Yasin, Megat Al Imran
    Sim, Ng Boon
    SAGE OPEN, 2024, 14 (03):
  • [25] Advising college students with dis/abilities in online learning
    Israel Reyes, Jose
    Meneses, Julio
    DISTANCE EDUCATION, 2022, 43 (04) : 526 - 542
  • [26] Antecedents and consequences of college students' satisfaction with online learning
    Um, Nam-Hyun
    Jang, Ahnlee
    SOCIAL BEHAVIOR AND PERSONALITY, 2021, 49 (08):
  • [27] Research on college students' emotional experience in online learning
    Wang, Lifeng
    Ye, Zi
    Zhu, Shaotong
    INTERNATIONAL JOURNAL OF CONTINUING ENGINEERING EDUCATION AND LIFE-LONG LEARNING, 2023, 33 (06) : 523 - 535
  • [28] A structural equation model predicting adults’ online learning self-efficacy
    Noriel P. Calaguas
    Paolo Maria P. Consunji
    Education and Information Technologies, 2022, 27 : 6233 - 6249
  • [29] Continuance Intention to Use Bilibili for Online Learning: An Integrated Structural Equation Model
    Liu, Xindi
    Yu, Zhonggen
    INTERNATIONAL JOURNAL OF ADULT EDUCATION AND TECHNOLOGY-IJAET, 2023, 14 (01):
  • [30] A structural equation model predicting adults' online learning self-efficacy
    Calaguas, Noriel P.
    Consunji, Paolo Maria P.
    EDUCATION AND INFORMATION TECHNOLOGIES, 2022, 27 (05) : 6233 - 6249