4.7 Article

Determinants of the digital outcome divide in E-learning between rural and urban students: Empirical evidence from the COVID-19 pandemic based on capital theory

Journal

COMPUTERS IN HUMAN BEHAVIOR
Volume 130, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chb.2021.107177

Keywords

Digital divide; E-learning; Capital theory; Cultural capital; Social capital

Funding

  1. National Natural Science Foundation of China [71771097, 71810107003]
  2. Humanities and Social Sciences Foundation of the Ministry of Education [17YJA630140]
  3. National Social Science Fund of China [18ZDA109]

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This study investigates the digital outcome divide between rural and urban students during the COVID-19 pandemic and identifies the main factors contributing to this divide. The findings suggest that differences in habitus and various forms of capital play a significant role in the digital outcome divide.
Digital outcome divide, the inequality of the outcomes of exploiting and benefitting from the ICT access and usage, has been raised as a severe concern of the e-learning practices during the COVID-19 pandemic. This study drew on capital theory and related literature and conducted a survey of 492 Chinese middle school students to explore: (1) whether a digital outcome divide exists between rural and urban students under the e-learning condition during the COVID-19 pandemic; (2) if it does, how does students' every form of capital impact the digital outcome divide. Our results revealed several important findings. First, we confirmed the existence of the digital outcome divide between rural and urban students, as rural students reported lower levels of behavioral engagement in e-learning courses compared to their urban peers. Second, we found that differences exist between rural and urban students in habitus (i.e., intrinsic motivation) and forms of capital, including cultural (i.e., e-learning self-efficacy) and social capital (i.e., parental support and teacher support), which are the main causes of the digital outcome divide. Third, a Blinder-Oaxaca decomposition analysis further confirmed that those factors could explain the major parts of the digital outcome divide between urban and rural students and that e learning self-efficacy, intrinsic motivation, and parental support were the most dominant factors contributing to the rural-urban digital outcome divide in the e-learning context. Our study provides several important theoretical and managerial implications for researchers and educators.

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