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Record W4396870111 · doi:10.1080/10447318.2024.2348227

Collaborative Skills Training Using Digital Tools: A Systematic Literature Review

2024· article· en· W4396870111 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Human-Computer Interaction · 2024
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
FundersPrix Inspiration ArctiqueMinistère de l'Enseignement supérieur, de la Recherche et de l'Innovation
KeywordsSystematic reviewPsychological interventionSocial skillsComputer scienceMedical educationPsychologyKnowledge managementData scienceMEDLINEMedicine

Abstract

fetched live from OpenAlex

The development of information and communication technologies has changed our way of working, emphasizing the need for individuals to develop collaborative skills. The aim of the present systematic review was to examine the extent to which these skills can be developed through the use of digital tools. A search of seven electronic databases, following PRISMA guidelines, yielded 18 relevant peer-reviewed articles. Analysis of the literature revealed that digital tools have the potential to enhance collaborative skills. However, the effects vary considerably, depending on which tools, methods, and measures are used. It also revealed that studies were conducted mainly in the social sciences, mostly among students, and half of them focused on short interventions. Another finding was that little is known about the features of the digital tools that actually contribute to these effects. Work on how digital tools contribute to the development of collaborative skills is still in its infancy, and more research based on rigorous methods and measures is needed.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.066
GPT teacher head0.456
Teacher spread0.390 · 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