Evaluating reflective writing to guide curricular improvements in health informatics education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of reflective essays to guide curricular improvements is explored in this qualitative study of two cohorts of students enrolled in a graduate health informatics course. The research questions, methods, and analysis were co-designed with the course instructor and a student who had completed the course and was a teaching assistant in the subsequent year. We thematically analyzed 95 anonymized student reflective essays with a taxonomy of learning and codes developed using the assignment rubric and similar themes derived from published literature. Major themes that emerged were (1) foundational knowledge acquisition and understanding, (2) integration and critical reflection, (3) self-discovery and imagining possibilities beyond the course, and (4) sharing and the human dimension. The results reinforce strengths of the course and informs areas for curricular improvement that incorporate reflection as part of a summative assessment. The discussion highlights challenges students had in writing reflective essays, which will be used to refine the activity and the instructions for the assignment. Our findings will assist students in developing their reflective practice to carry forward in their experiential internship in the program and their careers.
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.
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 | 0.012 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it