First Nations students’ perceptions of the enablers of and barriers to success in Australian higher education: a systematic review
Bibliographic record
Abstract
Abstract This article offers a systematic review of what the literature tells us about how First Nations students perceive the factors that contribute to or hinder their success in Australian higher education. It builds on the ‘Aboriginal Voices’ project that investigated the many and varied issues that have contributed to the underachievement of First Nations students in Australian schools. Focusing on research published between 2010 and 2020, we examine the key enablers of and barriers to Indigenous student success at university, concentrating on the views of Indigenous students themselves. This review highlights that this topic is crucially divided between the motivation and mobilisation of First Nations students and the fixed institutional and cultural structures through which they move. The review concludes that the primary barriers to Indigenous success in higher education are racism and whiteness in universities, and socioeconomic disadvantage in Indigenous communities; the primary enablers of Indigenous success are family and community support, Indigenous-specific support services, peer support and mentoring, and trusting and supportive relationships with university staff.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".