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Record W2738233869 · doi:10.1177/2379298117720444

Tools for Teaching Virtual Teams: A Comparative Resource Review

2017· article· en· W2738233869 on OpenAlex
Barbara Larson, Opal Leung, Kenneth Mullane

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

VenueManagement Teaching Review · 2017
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsAsynchronous communicationTask (project management)Virtual teamWork (physics)Computer scienceVirtual machineKnowledge managementResource (disambiguation)Instructional simulationEngineering managementVirtual realityHuman–computer interactionEngineeringSystems engineering

Abstract

fetched live from OpenAlex

As the ubiquity of virtual work—and particularly virtual project teams—increases in the professional environment, management and other professional programs are increasingly teaching students skills related to virtual work. One of the most common forms of teaching virtual work skills is a virtual team project, in which students collaborate with each other at a distance (and sometimes between multiple institutions) to accomplish a shared task. These projects differ from most management topics in their technology requirements. In this comparative review, we describe the features and trade-offs inherent in some of the asynchronous and synchronous communication technology tools commonly used to run virtual team projects.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.728
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.416
Teacher spread0.343 · 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