‘Trying to open the doors’: The co-creation of digital resources for disadvantaged primary school pupils
Bibliographic record
Abstract
This article explores the use of co-creation as an approach for involving university students in the development of educational initiatives for widening participation (WP) in higher education (HE) during the COVID-19 pandemic. At present, research and guidance looking at how co-creation practices can enable the production of such initiatives within HE is highly limited, which can deter others from employing this approach. To this end, we provide a case study of a WP project called Topic in a Box that involved staff and students working together to produce digital learning material for primary schools and students over several months. Through the use of semi-structured interviews with nine students, this research provides insight into the steps that were taken to develop the project, capturing the motivations, benefits and challenges of co-creation practice from a student perspective. We argue that this mode of co-creation should be used to a greater extent across the university sector and in recognition that university students have much to offer in terms of widening access to university.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".