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Record W2982038257 · doi:10.5539/jedp.v9n2p158

The Impact of Enhanced Teammate Evaluations on Important Individual and Team Outcomes

2019· article· en· W2982038257 on OpenAlexvenueno aff
Erik R. Eddy, Caroline P. D’Abate, Melinda L. Costello

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2019
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsTeamworkEnthusiasmInterpersonal communicationCurriculumPsychologyPerceptionInterpersonal relationshipMedical educationPedagogySocial psychologyMedicineManagement

Abstract

fetched live from OpenAlex

There is evidence that teamwork is proliferating in organizations and, in many ways, is replacing working individually. Academia has responded by integrating teamwork into curricula, but the use of teams as a pedagogical approach is also driven by evidence that it can lead to enhanced learning and more engaged learners. Researchers have examined factors in team effectiveness, activities and assignments for student teams and ways to optimize team formation. The current study was designed to focus on an under-explored and critical area of managing teamwork in classroom pedagogy: peer feedback. Students were placed into two conditions - a “conventional” approach using general, non-benchmarked feedback and an “enhanced” behaviorally-specific, benchmarked approach. Findings suggest enhanced teammate evaluations held substantial benefits over conventional evaluations resulting in better student perceptions of team processes (i.e., action, transition, and interpersonal processes) as well as more enthusiasm for teamwork. These findings have important implications for classroom pedagogy and student career development.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.026
GPT teacher head0.413
Teacher spread0.386 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2019
Admission routes1
Has abstractyes

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