Taking Social Entrepreneurship Education to the Next Level – A Teaching and Learning Project at Renaissance College (University of New Brunswick)
Bibliographic record
Abstract
In this paper we present the results of a scholarship of teaching and learning research project we conducted in 2016/17 at Renaissance College, University of New Brunswick. Our case study describes the challenges and successes of the student-centered re-design of a course about social entrepreneurship, a mandatory component of an undergraduate interdisciplinary leadership program. In particular, the project aimed at improvingStudents' engagement, andStudents' satisfactionparticularly for students who start the course at a lower engagement level.We first systematically evaluated pre-existing data on earlier runs of the course. Then we conducted interviews and a focus group with graduates in 2016 which provided additional information. The analysis of this dataset informed our comprehensive and systematic evidence-based redesign of the course for the offering in the winter of 2017. Finally, we used targeted surveys in March 2017 that provided data on the results of the course redesign and on student learning.In summary, the data suggested that the redesign of this course has significantly improved students’ learning experience, the clarity of course requirements, and students’ self-directed learning. This paper may be helpful also for scholarship of teaching and learning projects in other fields of study aiming at adult learner oriented and evidence-based course redesign.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".