Impact of global and local community involvement on curricular learning experience in university education
Bibliographic record
Abstract
We investigated the impact of various curricular opportunities on the learning experience of university students. We believe that determining the most valuable part of each opportunity as identified by students will help align out-of-classroom and in-class learning experiences. Students in Fundamentals of Human Anatomy and Physiology (BIO210) at University of Toronto Mississauga were offered four different curricular assessment options in September of 2016, including: 1. six term tests; 2. five term tests and a reflection based on science for public assessment; 3. five term tests and a reflection based on an international learning experience pilot to Peru; and, 4. five term tests and a reflection based on a community-engaged learning experience pilot. We used a validated post-survey to investigate the impact of the various curricular experiences in BIO210. Of the sampled students (N=73) in the international learning experience pilot, 28% strongly believed that they learned enough to have ideas that can address healthcare issues as compared to 7% in the local learning experience pilot (option 2 and 4) and 6% in option 1. Of the students participating in option 1, 85% of the students felt that they utilized their critical thinking skills as compared to 86% in groups that participated in local experiences (options 2 and 3) and 100% in option 4. Our preliminary findings suggest that students perceive international experiences as beneficial to their development outside the classroom. Specifically, embedding diverse out-of-classroom experiences were important for improving student utilization of evaluation and analysis skills as well as widening the scope of global perspectives among students.
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".