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A new study has developed a different way of analyzing NAPLAN data to gain a more nuanced understanding of Indigenous students' academic performance. The study used a quantitative method called "within-cohort, peer matching" to compare Indigenous students with their Indigenous peers from the same grade and geographical location. The analysis revealed patterns that would not have been obvious if only the disparity between Indigenous and non-Indigenous students' performance was considered. The findings challenge the traditional framing of Indigenous students as progressing poorly and highlight the need for alternative measures of Indigenous success. [Extracted from the article]

Data reporting in the Australian education system produces deficit-based comparisons of academic achievement between Indigenous and non-Indigenous students. Since 2009, data from the National Assessment Program – Literacy and Numeracy (NAPLAN) have been used by the Australian government to allow it to report on ‘Closing the Gap’ policy. These data are used to justify government-funded initiatives designed to improve educational outcomes for Indigenous students. While the logic of this approach has political cachet, the ‘gaps’ have persisted. Instead, we propose using ‘within-cohort, peer matching’ quantitative methods to achieve such aspirational goals. Using publicly available NAPLAN data, we examined patterns of relative performance within the cohort of Indigenous students. We assessed trends in Indigenous students’ performance in NAPLAN relative to their Indigenous peers across grades (3, 5, 7, and 9), states and territories, remoteness categories, and calendar years from 2010 to 2019 inclusive. Key insights available through this approach include detailed patterns of higher and lower relative performance for Indigenous students within matched remoteness categories, across states and territories, and over time, laying the groundwork for further analyses of the local, systemic, and school-level factors associated with these differing outcomes. Our methods provide novel findings that justify changing the deficit assumption, supporting the use of within-cohort peer matching instead.