Academic writing among first-term students in the nursing programme at the Swedish Red Cross University College − A description of a three-term transprofessional project in collaboration with the library and the student support unit at Södertörn University
Bibliographic record
Abstract
Background and objectives: The academization of the nursing education has emphasized the need for students to acquire academic literacies both for educational and clinical reasons. However, for long being a practical profession, nurse students do not always reflect on the importance of being academic literate. This aim of this article was to describe the teaching of introductory academic writing to first-term students in the Swedish Red Cross University College’s nursing programme, implemented as a transprofessional collaboration project involving the Swedish Red Cross University College and the library as well as the student support unit at Södertörn University.Methods: A model was used for implementing teaching of academic literacies to first-term nursing students embedded in a discipline-specific course. The model consisted of two seminars, one introductory seminar focusing on academic writing and how to search for, read, appraise, and use research articles and one feedback seminar. Peer feedback was performed by the students. In between the seminars, the students began to work on their course assignment and later finalized the assignment using the feedback provided by teachers and peers.Results: The transprofessional collaboration in teaching academic literacies was described as successful. Teachers and students found the embedding of academic writing in a subject-specific course as useful, although – from a student perspective – demanding and partly difficult. The provision of feedback was regarded as helpful and encouraged the students to finish their assignments. Although being a team of teachers, the large class sizes resulted in an extensive workload and stressful situations. Yet another challenge, important for the sustainability of the model, was to win support for teaching academic literacies among all teachers in the nursing programme.Conclusions: The transprofessional collaboration when teaching academic literacies to first-term nursing students have indicated advantages and challenges, of which both are of importance to consider carefully in the further planning and implementation of the project.
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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".