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Record W4396218587 · doi:10.1145/3653696

Field Trial of a Tablet-based AR System for Intergenerational Connections through Remote Reading

2024· article· en· W4396218587 on OpenAlexaff
Ye Yuan, Peter Genatempo, Qiao Jin, Svetlana Yarosh

Bibliographic record

VenueProceedings of the ACM on Human-Computer Interaction · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsMcMaster University
FundersUniversitas Brawijaya
KeywordsSocial connectednessReading (process)Field (mathematics)Context (archaeology)Work (physics)Computer scienceKnowledge managementPsychologyEngineeringSocial psychologyGeographyPolitical science

Abstract

fetched live from OpenAlex

Prior work has explored various technology designs to support intergenerational communications and connections through remote activities such as reading or play. However, few works have explored these technologies outside the family settings. In this work, we aimed to understand how technology can support social connectedness through remote activities, by investigating the use of a tablet-based AR system among older adult volunteers and students for remote reading. We developed the system based on insights from previous research, deployed the system in the field, and observed the use of the system over six months. With the data collected from the field, we present a rich description on the use of the system and the practices that emerged around its usage in a real-world setting. Our findings highlight the importance of supporting an engaging reading experience and context understanding for social connections with the technology design. We provide insights into how such technology can support intergenerational communication and foster social connectedness.

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)0.001
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: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
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 head0.370
Teacher spread0.305 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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