Team Building Through Team Video Games: Randomized Controlled Trial
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
Background Organizations of all types require the use of teams. Poor team member engagement costs billions of US dollars annually. Objective This study aimed to explain how team building can be accomplished with team video gaming based on a team cohesion model enhanced by team flow theory. Methods In this controlled experiment, teams were randomly assigned to a team video gaming treatment or a control treatment. Team productivity was measured during both pretreatment and posttreatment team tasks. After the pretest, teams who were involved in the team video gaming treatment competed against other teams by playing the Halo or Rock Band video game for 45 minutes. After the pretest, teams in the control treatment worked alone for 45 minutes. Then, all teams completed the posttest team activity. This same experimental protocol was conducted on 2 different team tasks. Results For both tasks, teams in the team video gaming treatment increased their productivity significantly more (F1=8.760, P=.004) on the posttest task than teams in the control treatment. Our flow-based theoretical model explained team performance improvement more than twice as well (R2=40.6%) than prior related research (R2=18.5%). Conclusions The focused immersion caused by team video gaming increased team performance while the enjoyment component of flow decreased team performance on the posttest. Both flow and team cohesion contributed to team performance, with flow contributing more than cohesion. Team video gaming did not increase team cohesion, so team video gaming effects are independent of cohesion. Team video gaming is a valid practical method for developing and improving newly formed teams.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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