Teaching with Cases in Disaster and Emergency Management Programs: Instructional Design Guidance
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
There is a long history of the use of cases in teaching in post-secondary programs and some fields (e.g., law, medicine, business) have their own distinctive approach to the use of case-based learning methods. Within disaster and emergency management (DEM), which is a relatively new field of post-secondary study, there are as of yet no formally recognized approaches to the use of cases in teaching, and further there is limited research on the disciplinary characteristics of teaching practices in the DEM field. This article presents findings from a study that explored how and why cases are used in post-secondary DEM programs. The methodological approach to the study supported the development of a domain-based outcome theory that explains three different approaches for using case-based learning methods in DEM programs and the functions of cases relative to each of the different types of learning outcomes. This novel conceptual framework for teaching with cases was found to address deficiencies in existing schema for conceptualizing the use of cases in teaching.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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