Attitudes Count But Are Insufficient To Close Systemic Inequalities In Digital Abilities

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Attitudes Count But Are Insufficient To Close Systemic Inequalities In Digital Abilities

People who earn low incomes. Those over the age of 65. Those with some disability. People who belong to an ethnic minority. What do all of these groups have in common? These are the social groups for whom digital and learning technologies are bound to generate the most impact. They are also the groups who are the most likely to be “digitally excluded.”

WIRIS

In its second year, the Australian Digital Inclusion Index shows measures of progress across three dimensions of digital inclusion: Access, Affordability, and Digital Ability. Although the last dimension deserves a special interest from the EdTech community, the high correlation reported suggests that efforts for more digital inclusiveness need to consider the three dimensions in conjunction.

The Digital Ability dimension is made up of three components:

  • Attitudes, identified with positive answers on control, enthusiasm, learning, and confidence.
  • Basic skills, encompassing general, phone, banking, shopping, community, and information skills.
  • Activities, which measure advanced ability mirroring the 6 Basic skills components.

According to the report, the Digital Ability dimension has improved at a significantly higher rate than the other two. In general terms, suspected factors such as distance from main cities or old age have a negative effect on the score. Women score lower than men on overall due to lower scores on Attitudes, despite their Basic Skills and Activities scores being higher, but the gap is small compared to other demographic attributes. Indigenous Australians report lower than average Digital Ability, but a higher score on the Attitude dimension.

For the development of the Australian Index, a methodological discussion paper was released in 2015, proposing a 0-to-100 (“perfectly digitally included”) score. Following a round of input, the final design was used to analyze a 50,000-response survey, from which 16,000 were used in the final calculation. Data was broken down by region, income, education, employment status, age, and eligibility for disability support. Instances of small samples are indicated across the findings.

Read this year’s report and access data at digitalinclusionindex.org.au.


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