Climate studies: can students’ perceptions of the ideal educational environment be of use for institutional planning and resource utilization?
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
As educational climate strongly affects student achievement, satisfaction and success, it is important to get regular feedback from students on how they experience the educational environment. The Dundee Ready Education Environment Measure (DREEM) Inventory was administered on the same day to all first-, second- and third-year students at the Canadian Memorial Chiropractic College (CMCC) and the students were requested to complete the questionnaire as they were actually experiencing the educational environment at CMCC, and then to say what they would have wanted, or preferred it to be like. Valid returns were received from 146 (95%) first-, 123 (82%) second- and 73 (48%) third-year students (n = 342). The results indicated that the DREEM Inventory used in the Ideal mode, together with the responses in the Actual mode, could be used effectively to determine the dissonance between what they had and what they would have liked to have. It was found that there was a strong similarity in the areas of the educational environment that the different groups of students indicated as falling short of their ideal. The results of this study provided a useful basis for strategic planning and resource utilization.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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