Diverse experiences and belonging in an online, first-year, team-based engineering design course
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
Cultivating a sense of belonging can be challenging in online contexts as well as for underrepresented students in engineering education. This study used a mixed methods sequential explanatory design to understand underrepresented students’ experiences in a Canadian first-year course. Taking place during remote delivery due to COVID-19, we surveyed students about constructs related to belonging and team experience, finding significant differences between men and women as well as between the majority social group (white and South Asian men) and their peers in terms of whether they valued the diversity of the teaching assistant (TA) team, and whether the course contributed to their sense of belonging in engineering. Follow up interviews shed light on some of the differences in students’ perceptions and experiences based on gender and ethnicity, and have implications for inclusive teaching strategies in first-year courses, in particular related to designing team activities and providing supports for peer-TA-instructor interactions.
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 | 0.003 | 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 | 0.000 |
| 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