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Record W1554008140 · doi:10.1080/10400435.2011.588990

Children's Satisfaction With Assistive Technology Solutions for Schoolwork Using the QUEST 2.1: Children's Version

2011· article· en· W1554008140 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueAssistive Technology · 2011
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
Fundersnot available
KeywordsSmileyAssistive technologyPsychologyApplied psychologyMedical educationMedicineComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

This study explored the levels of satisfaction children 8–18 years experienced with assistive technology items used to assist them in their schoolwork. Modified from the Quebec User Evaluation of Satisfaction (QUEST 2.0), the QUEST 2.1: Children's Version was developed to enable scoring by children with or without parent assistance. The QUEST 2.1: Children's Version used a seven-point smiley face scale (1 = “delighted”). A mailed survey to a convenience sample of 703 children with physical disabilities was undertaken with 156 responses (22.5% response rate) yielding 98 valid QUEST 2.1 questionnaires. Children had a mean age of 12 years 6 months (SD 3.0 years), 60.2% were boys, and 80.6% resided in metropolitan or peri-urban areas. For data analysis, assistive technology items were grouped as communication devices, computer hardware, computer software, and other. High levels of satisfaction were reported overall on the QUEST 2.1: Children's version (total score mean 2.66, SD 1.09). Variations between different groups of assistive technology items, and between items indicated as most or lest favorite are reported and discussed. Advice given for selection, reliability, and ease of use were identified as the most important satisfaction items.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesScience and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0050.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.002
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 head0.369
Teacher spread0.302 · 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