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Record W2762181356 · doi:10.1080/02602938.2017.1380161

Team dynamics feedback for post-secondary student learning teams

2017· article· en· W2762181356 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAssessment & Evaluation in Higher Education · 2017
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsUniversity of OttawaUniversity of Calgary
Fundersnot available
KeywordsPsychologyTeam compositionTeam effectivenessContext (archaeology)Medical educationHealth careTeamworkSuitePerceptionApplied psychologyKnowledge managementComputer scienceMedicineSocial psychology

Abstract

fetched live from OpenAlex

In the current research, we introduce the team CARE model for supporting team development during post-secondary education. Team CARE is part of a larger suite of assessments at itpmetrics.com. Team CARE is a free, online, survey-based assessment that allows team members to rate their team’s health and functioning in four key categories (communicate, adapt, relate and educate), as well as provide written feedback about the team’s functioning to add nuance and supplemental context to the numeric scores. Team members completing the assessment receive a report documenting their team’s scores on the variables measured. We report on data from student learning teams suggesting that the variables in the team CARE model are reliable, and that they are correlated with team performance outcomes. Students’ perceptions of the tool were also examined, and the findings suggest that team CARE is perceived to be valuable, useful and easy to use. Recommendations for practice are detailed, including sample assessment schedules for teams with differing life spans. Implications for future research and implementation are discussed.

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.

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)0.002
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 score0.230
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0030.000

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 head0.047
GPT teacher head0.461
Teacher spread0.414 · 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