Individual learning and group performance: the role of collective efficacy
Bibliographic record
Abstract
Purpose The aim of the current study is to investigate the effect of training individual group members on the collective efficacy of the group and the group's subsequent performance. Design/methodology/approach Participants (n=275), in a laboratory study were randomly assigned to groups of five (k=55). Individuals were then randomly selected from those groups such that none, one, three, or all five members of the group participated in training on effective ways to select a job candidate. Findings Groups in which at least a majority of group members were trained had higher collective efficacy than groups where fewer members were trained. Training individuals beyond a majority did not improve collective efficacy further. Collective efficacy mediated the relationship between individual training and group level performance. Research limitations/implications This research extends the knowledge of the relationship between the individual and the group within social cognitive theory. Training a majority of the group is needed to see an increase in collective efficacy, a mediator of group performance. Practical implications Human resource managers should consider the effects of training individuals when they expect their employees to work as teams. It is beneficial to train as many people as necessary for the group to be able to benefit from the new information; however, training beyond the majority of people within the group does not improve confidence or performance. Originality/value The paper examines the relationship between individual group members and collective efficacy in a learning context. This extends the knowledge of social cognitive theory by crossing levels of analysis.
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 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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".