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Record W4416702536 · doi:10.1145/3773967.3773973

Supporting Older Adults' Software Learning via Live Assistance and Guided Mockup

2025· article· en· W4416702536 on OpenAlexaff
Teerapaun Tanprasert

Bibliographic record

VenueACM SIGACCESS Accessibility and Computing · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAsynchronous communicationSoftwareAsynchronous learningAssistive technologyEducational technologyAssisted living

Abstract

fetched live from OpenAlex

Older adults are increasingly integrating technology into their daily lives but often need guidance to navigate new tools effectively. Some benefit from real-time support from family members, while others prefer self-paced, asynchronous help. To meet their diverse needs, I propose two solutions: HelpCall and SoftBox. HelpCall provides synchronous guidance through an assistive video overlay, helping older adults follow instructions from remote family members. In contrast, to support asynchronous assistance, SoftBox generates guided interactive software mockups from screencast demonstrations to allow learners to independently explore and learn new features in a sandbox-like environment. Through user studies with older adults and their family members, these projects offer complementary insights into synchronous and asynchronous support, advancing accessible technology for diverse learning needs and contexts and moving toward universal accessibility in digital tools.

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)0.002
metaresearch head score (Gemma)0.007
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.014
GPT teacher head0.339
Teacher spread0.325 · 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.

Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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