Case study: Digital inclusion, low-income families, and online education in the wake of the COVID-19 pandemic

A single mother assisting her daughter using a tablet device

This case study was originally published in the 2020 Australian Digital Inclusion Index report, and is derived from the Roy Morgan Single Source dataset. As of 2021, the Australian Digital Inclusion Index is based on the Australian Internet Usage Survey (AIUS). The numerical results of this case study cannot be compared with the refreshed ADII data.

As schools physically closed around the country in response to the COVID-19 pandemic there were varied experiences of home-schooling from families with different levels of digital inclusion.

While the transition to online education was a significant change for most families, digitally excluded cohorts, such as low-income families with school-aged children, faced specific challenges to accessing their lessons online1. These challenges will have ongoing consequences for many students.

There are just under four million primary and secondary students in Australia2. Approximately 800,000 of these students, or 20%, are from households in the lowest income bracket (earning under $35,000 per annum)3. These households record an Index score of 52.9. This is 10.1 points lower than the national average (63), and 15.5 points lower than families with school-aged children in other income brackets (68.4).

Low-income families with school-aged children are relatively disadvantaged across all three digital inclusion dimensions. Low-income families lack access to appropriate devices, pay more for their digital services than others, and have lower digital skills. When combined with what we know about educational inequality4, digital exclusion will have an ongoing negative impact on the educational outcomes of students from these families. When students from lower socioeconomic families fall behind at any point, they are less likely than others to catch up again5.

Low-income families receive an Index score of 74.6 for Access, 1.7 points lower than the national average, and 7.3 points lower than all families with school-aged children.

Low-income families with school-aged children are also less likely to have access to individual devices adequate for online education during lockdown schooling6. These households have on average half as many desktop, laptop or tablet computers as middle-income households7.

Although low-income families are much less likely than other Australian households to have internet access at home8, they are likely to have access to more data than the national average. While low-income families are 7.2 points behind other families with school-aged children in terms of Internet Data Allowance (receiving an Index score of 59.3, compared with 66.5), the national average is 58.7. This is likely because data access is perceived as essential for contemporary school, work, and leisure tasks9. This access, however, comes at a high cost.

Affordability is the greatest barrier to digital inclusion for low-income families with school-aged children10. These families spend 5.30% of their household income on internet access each month. This is in comparison to the 1.09% spent by families with school-aged children in other income quintiles, and the 1.16% spent nationally. Low-income families are highly reliant on mobile-only access11. Where 19.9% of the Australian population are mobile-only internet users, this jumps to 33.5% of low-income families with school-aged children. As a consequence, low-income families score 35.6 for Affordability. This is a massive 29.8 points lower than other families with school-aged children, and 25.3 points lower than the national average.

Parents in low-income families are less likely than parents in other income quintiles to have the digital skills required to support their children’s online schooling12. Although the ADII does not specifically capture the digital skills of students, there are significant known disparities based on socio-economic status. Low-income families record an ADII score of 48.5 for Digital Ability, 3.5 points lower than the national average (52), and 9.4 points lower than other households with school-aged children (57.9).

Students from low-income families report significantly lower scores in digital reading literacy13. These students lack the more advanced digital skills that would allow them to work in the independent manner that online education during a pandemic requires14. While the low Digital Ability scores received by parents in low-income families restricts their capacity to support school-aged children in their online education, they are also more likely to be an essential worker and therefore less likely to be able to work from home15. Furthermore, students with parents with low levels of education attainment, not in paid work or employed in low skill occupations, Indigenous students, and those students from regional and remote areas report significantly lower Digital Ability scores than the national average16.

Understanding the impact of COVID-19 and online education

Low-income families with school-aged children are highly likely to have experienced complex and compounded digital exclusion during COVID-19 lockdowns. These families lack access to both technology options and suitable devices, pay more of their household income for these digital services than others, and have lower digital skills, creating significant challenges for adapting to an online learning environment.

Low-income household families are differentially impacted by online learning depending on where they reside. Australian state authorities have ordered physical school closures at different times and for different durations, whilst (at the time of writing) schools in SA remained fully operational throughout.

As the pandemic progresses, states are modulating physical school closures within local government areas in response to community transmission rates117. Those in affected areas find themselves thrust into, or back into, fully online learning at short notice. The impact of COVID-19 on the education of children in low-income families is therefore not uniform. A range of government, telecommunications and community initiatives have been launched in the wake of the pandemic to try and address this digital inequity. However, there is clearly a need for more coordinated long-term investment in improving digital inclusion for low-income households.
The implications of these impacts are deeply concerning. Unless provided immediate and significant support, these 800,000 students are less likely than their counterparts to return to a successful educational pathway18. Given the potential of ongoing lockdowns19, mitigating the adverse effects of digital exclusion for students from low-income families will be critically important for the foreseeable future.

Further information

For more information, including related data tables and the full citation list, please refer to the 2020 Australian Digital Inclusion Index.

References and footnotes

[1] Flack et. al. (2020); Robinson et al., (2020).

[2] ABS (2019).

[3] ABS (2019); Drane et. al. (2020).

[4] Australian Council for Educational Research (2020); Bonnor & Shepherd (2016); Cassells et. al. (2017); Chesters (2019); Noble et. al. (2020); Perry & McConney (2010).

[5] Brown et. al. (2020); Clinton (2020); Doyle (2020); Drane et. al. (2020); Duffy & Kent. (2020); Education Endowment Fund (2020); Lamb et. al. (2015); Markham, Smith, & Morphy (2020).

[6] Rapid Research Information Forum (2020); Flack et al. (2020); Drane et al. (2020).

[7] Rapid Research Information Forum (2020); Australian Bureau of Statistics (2018b).

[8] Australian Bureau of Statistics (2018b); Noble (2020); The Smith Family (2020); The Smith Family (2013).

[9] Ogle & Musolino (2016).

[10] Ogle (2017).

[11] Ogle & Musolino (2016).

[12] Flack et al. (2020).

[13] Thomson & De Bortoli (2012).

[14] Fraillon (2019); Fraillon. (2020).

[15] Noble et al. (2020).

[16] Australian Curriculum, Assessment and Reporting Authority (2018).

[17] Flack et al. (2020).

[18] Noble. (2020); Flack et al. (2020).

[19] Chowdhury et. al. (2020).


Thomas, J, Barraket, J, Wilson, C, Ewing, S, MacDonald, T, Tucker, J & Rennie, E, 2020, Measuring Australia’s Digital Divide: The Australian Digital Inclusion Index 2020, RMIT University, Melbourne, for Telstra. DOI:

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