Partnering with Students to Develop a Capstone for a Graduate Health Informatics Program
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
OBJECTIVE: This study aimed to assess the desirability, feasibility, and sustainability of integrating a project-based capstone course with the course-based curriculum of an interdisciplinary MSc Health Informatics program guided by a student-partnered steering committee and student-centered approach. METHODS: = 18) of health informatics students and alumni. Survey data were analyzed descriptively. Focus groups were audio-recorded and transcribed verbatim and then analyzed using a general inductive and classic analysis approach. RESULTS: Most students supported including a capstone project but desired an option to work independently or within a group. Students perceived several benefits to capstone courses while concerned over perceived challenges to capstone implementation, evaluation, and managing group processes. The themes identified were (1) professional development, identity, and career advancement, (2) emulating the real world and learning beyond the classroom, (3) embracing new, full-circle learning, (4) anticipated course structure, delivery, and preparation, (5) balancing student choice, interests, and priorities, and (6) concerns over group dynamics, limitations, and support. CONCLUSION: This study demonstrates the value of having students as partners at each stage in the process from methods conception to course curriculum design. With the steering committee and the curriculum developer, we codeveloped a student-centered course that integrates foundational digital health-related project knowledge acquisition with an inquiry-based project that can be completed independently or in small groups. This study demonstrates the potential benefits and challenges that health informatics educators may consider when (re)designing capstone courses.
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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 | 0.024 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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