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Record W2946432939

Freshman Fitteen: Effects of an online team building exercise intervention

2013· article· en· W2946432939 on OpenAlexaff
Christopher K Forrest, Mark W. Bruner

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsNipissing University
Fundersnot available
KeywordsCohesion (chemistry)Psychological interventionPsychologyGroup cohesivenessContext (archaeology)Task (project management)Intervention (counseling)Applied psychologyPhysical therapyMedical educationSocial psychologyMedicineEngineering
DOInot available

Abstract

fetched live from OpenAlex

Previous research revealed positive relationships between team building (TB), cohesion, and group task satisfaction in exercise settings (Bruner & Spink, 2011; Carron & Spink, 1993). However, researchers have yet to examine the efficacy of an online TB intervention to foster these constructs in a similar activity context. The purpose of this pilot study was to examine the effectiveness of an 8-week online TB intervention, Freshman Fitteen, designed to enhance group cohesion, group task satisfaction and physical performance in first year university students. Twenty-seven participants (Mage=18.6, SD =1.3) completed questionnaires assessing cohesion and group task satisfaction and a series of physical fitness tests at baseline and following the completion of the 8-week intervention. After controlling for baseline assessments, results revealed significant increases in cohesion (ATG-T, ATG-S and GI-T), group task satisfaction and two measures of physical fitness (push-ups and vertical jump height) (ps. <.05). These findings extend previous TB research to an online platform and provide preliminary support for the use of online TB interventions as an effective group-based strategy designed to promote group cohesion, group task satisfaction and physical performance in an exercise setting. Acknowledgments: The project was supported by the Schulich School of Education, Nipissing University.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.011
GPT teacher head0.301
Teacher spread0.290 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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