Valuing Arts-Based Academic Projects in a Faculty of Nursing: Experiences of Graduate Students and Supervisors
Bibliographic record
Abstract
Purpose: The purpose of this article is to explore student and supervisor experiences and perspectives regarding the advantages and challenges of arts-based projects in the context of graduate nursing education programs. We define arts-based academic projects as graduate level projects that incorporate a significant artistic component, and that culminate in a final written report of a capping exercise, a thesis or a dissertation. Procedures: Three graduate students were asked to briefly summarize their arts-based academic projects and to reflect upon their experiences with their projects, noting the advantages and challenges that they encountered in the process. The students’ supervisors also reported their experiences with supervising students conducting arts-based academic projects. The resulting written reflections were collated and summarized. Results: The arts-based academic projects included a set of comics, a story-based digital education tool and a digital knowledge whiteboard animation video. All of these projects integrated visual art into products for the purpose of knowledge translation. The students and their supervisors identified numerous advantages to arts-based projects, such as being able to address the complexities of context and to engage broad audiences. They reported challenges such as misunderstanding and devaluing the nature of these less traditional academic projects. Conclusions: This study has implications for future arts-based projects that may be conducted in Schools or Faculties of Nursing. Supervisors and committee members play a key role in fostering the creativity of students, building on their strengths, and encouraging them to pursue innovative theses or capping exercises. Similarly, graduate program coordinators/associate deans of graduate programs can also support these students by encouraging and approving projects that are less conventional and by helping others understand the value of these projects.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| 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".