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Record W2029432110 · doi:10.1145/2660398.2660402

Exploring How a Co-dependent Tangible Tool Design Supports Collaboration in a Tabletop Activity

2014· article· en· W2029432110 on OpenAlexafffund
Min Fan, Alissa N. Antle, Carman Neustaedter, Alyssa Friend Wise

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsSimon Fraser University
FundersNetworks of Centres of Excellence of CanadaSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceHuman–computer interactionPoint (geometry)Co-designCollaborative designAction (physics)Work (physics)Knowledge managementSystems designSoftware engineeringEngineeringComputer architecture

Abstract

fetched live from OpenAlex

Many studies suggest that tangibles and digital tabletops have potential to support collaborative interaction. However, previous findings show that users often work in parallel with such systems. One design strategy that may encourage collaboration rather than parallel use involves creating a system that responds to co-dependent access points in which more than one action is required to create a successful system response. To better understand how co-dependent access points support collaboration, we designed a comparative study with 12 young adults using the same application with a co-dependent and an independent access point design. We collected and analyzed categories of both verbal and behavioural data in the two conditions. Our results show support for the co-dependent strategy and suggest ways that the co-dependent design can be used to support flexible collaboration on tangible tabletops for young adults.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
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 head0.065
GPT teacher head0.285
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations25
Published2014
Admission routes2
Has abstractyes

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