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Record W4404173321 · doi:10.1145/3687031

Designing Collaborative Technology for Intergenerational Social Play over Distance

2024· article· en· W4404173321 on OpenAlexafffund
Ye Yuan, Qiao Jin, Chelsea Mills, Svetlana Yarosh, Carman Neustaedter

Bibliographic record

VenueProceedings of the ACM on Human-Computer Interaction · 2024
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsMcMaster UniversitySimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSociologyComputer science

Abstract

fetched live from OpenAlex

Collaborative play not only provides entertainment but also nurtures connections and strengthens community ties. In family and intergenerational contexts, collaborative activities and play can engage family members in quality conversations and meaningful connections over distance. To explore participants' preferences, practices, and interaction dynamics when playing remotely, we conducted a design probe study with 15 groups of parents and children from 16 families. Our findings highlight both similarities and notable differences in the use of communication methods, workspaces, and objects between parents and children. Specifically, we observed distinct patterns in gestural and verbal communication and identified specific challenges encountered by children in a simulated remote setting. Our findings also revealed the dynamics of play sessions, particularly when co-located participants are involved, shedding light on the complexities of remote intergenerational communication and play. Our work contributes empirical insights into designing more effective and engaging remote collaborative platforms for families.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.589
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.038
GPT teacher head0.344
Teacher spread0.306 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2024
Admission routes2
Has abstractyes

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