Reflection as a Window to Student Development: Insight for Faculty, Preceptors, and Mentors
Bibliographic record
Abstract
This article is the third in a series of five articles explaining the grounded theory named RESPoND: Reflection in the Education and Socialization of Practitioners: Novice Development. Participants in the grounded theory study included a cohort of audiology students, clinical faculty, and preceptors. This particular article focuses on the first of three facets that together explain the role of reflection in novice development, in the context of the RESPoND theory. This facet represents the concept of reflection as a window—for faculty, preceptor, and mentor insight—into student and novice development. The notion of reflection as a professional development approach or mechanism for learners or professional practitioners is well documented. However, there is a lack of theorization about how reflection by health professional students may present opportunities for their faculty, preceptors, and mentors to improve their educational approaches. Findings are discussed in the context of implications for audiology education. We acknowledge that these findings relate specifically to the participant cohort; however, the understanding gained from this research may nonetheless be informative to a wide audience of individuals interested in audiology education.
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 | 0.029 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.011 | 0.019 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| 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".