Mature students’ journey into higher education in the UK: an interpretative phenomenological analysis
Bibliographic record
Abstract
This article reports on issues of diversity in the context of widening participation in global higher education (HE). Mature students represent a third of the HE student population in Australia, Canada, UK and the USA. More research is needed to understand factors that can facilitate or hinder access to HE for this group. The aim of this study was to examine factors that a small group of mature students perceived influenced them as they made the decision to take up HE. Six undergraduate students at a British university who were on track to finish their studies took part in semi-structured interviews. All participants were white and from families with no previous experience of HE. Mean age was 42.7 years (range 35–51), and 50% were female. The interviews were analysed using Interpretative Phenomenological Analysis. Through using phenomenological analysis to analyse perceptions of changing motivation and goals during the decision-making process to take up HE, a detailed understanding of the complexity of these change processes was obtained. The analysis offers evidence that mature students experience far-reaching personal and social changes related to their decision to enter HE and adds a novel understanding of these identity-changes. This new insight is of fundamental importance to the field because the novel understanding of mature students’ meaning-making could be used to tailor interventions to facilitate access to HE for mature students.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".