The effects of behavioural outcome goals, learning goals, and urging people to do their best on an individual's teamwork behaviour in a group problem-solving task.
Bibliographic record
Abstract
La recherche recente demontre que les buts d'apprentissage sont superieurs aux buts axes sur les resultats dans le contexte de tâches complexes. L'efficacite des buts axes sur les resultats comportementaux (etablis a l'aide d'une echelle d'observation comportementale), les buts d'apprentissage et l'incitation des personnes a faire de leur mieux ont ete examines dans le contexte d'un programme d'apprentissage destine a ameliorer le comportement individuel en equipe dans le cadre d'une tâche de resolution de probleme en groupe. Les participants (n = 50) qui ont etabli des buts comportementaux ou des buts d'apprentissage ont connu une plus grande autoefficacite que ceux qui avaient ete incites « a faire de leur mieux ». L'autoefficacite entrait en correlation positive avec le comportement en travail d'equipe et l'engagement envers un but. Ces conclusions suggerent que les buts axes sur les resultats comportementaux peuvent attenuer la necessite d'imposer des buts d'apprentissage dans le cas de tâches complexes.
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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 | 0.004 | 0.017 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".