VALUE OF LANGUAGE BACKGROUND ON IDEA GENERATION SESSIONS IN FIRST-YEAR ENGINEERING DESIGN TEAMS
Bibliographic record
Abstract
Abstract – An ongoing debate around classroom organization decisions, particularly with regard to team formation, involves the value associated with team-member diversity. Diversity can be defined, for example, in terms of discipline, marks, race, gender, language, age, experience, or goals. For the researchers in this case, this debate around the impact of diversity motivated further analysis of just what, if any, impact linguistic diversity had on teams in first-year engineering design courses. This is of particular concern given the dramatic increase in the percentage of multilingual students that make up current student bodies across Canada. Our analysis indicates that the effect of having non-native speakers of English (NNSE) on a team is not a de facto detriment to idea generation and discussions within the team. Thus, this paper reports on the effects of multilingualism on team dynamics and idea generation. The authors present here a subset of the data from of a much larger study on effective teamwork behaviours, that highlights two multilingual dominant teams from the larger study. The analysis examines how multilingualism and values associated with it contributed to and developed an integrated understanding of both the problem being addressed and potential solutions to that problem.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".