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Digital Divide in Education during COVID-19 Pandemic

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  • Surianshah, Sarimah

    (Faculty of Science and Natural Resources Universiti Malaysia Sabah Jalan UMS, 88400 Kota Kinabalu, Sabah MALAYSIA.)

Abstract

This study aims to examine the impact of digital divide on student outcomes using primary data. We used a sample of 233 secondary school students in the rural area of Sabah, Malaysia, during the COVID-19 pandemic from October to November 2020, about six months into student mandatory online learning. A random sampling method was employed in data collection using online questionnaire. This study adopted the two-step least squares method. We specifically measured students’ outcomes based on their perspectives of online class effectiveness and student financial constraints to attend these classes. The findings proved the existence of digital divide among students in rural areas. Specifically, the students’ low level of online learning attendance produced positive and statistically significant effect on their perspective of the effectiveness of online learning. In addition, the availability of digital devices at home significantly influenced student decision to take part-time jobs in order to help them purchase these devices to enable them attend classes. The findings suggest that there exist digital access barriers among students in rural areas during the pandemic. The study implies that the government or policymakers need to effect strategic intervention such as digital endowment to ensure that the digitally disadvantaged students are not left behind their peers.

Suggested Citation

  • Surianshah, Sarimah, 2021. "Digital Divide in Education during COVID-19 Pandemic," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 55(3), pages 103-112.
    • Handle: RePEc:ukm:jlekon:v:55:y:2021:i:3:p:103-112
    DOI: http://dx.doi.org/10.17576/JEM-2021-5503-07
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    References listed on IDEAS

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    More about this item

    Keywords

    Covid-19; digital divide; government intervention; rural area; student outcomes;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • I2 - Health, Education, and Welfare - - Education
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty

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