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Record W2967273694 · doi:10.1177/1539449219868276

Exploring Skills Gained Through a Robotics Program for Youth With Disabilities

2019· article· en· W2967273694 on OpenAlexaff
Sally Lindsay

Bibliographic record

VenueOTJR Occupational Therapy Journal of Research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsUniversity of Toronto
FundersDirectorate for STEM Education
KeywordsRoboticsThematic analysisPsychologyMedical educationDescriptive statisticsArtificial intelligenceQuality (philosophy)Educational roboticsApplied psychologyRobotComputer scienceMedicineQualitative researchSociologySocial scienceMathematics

Abstract

fetched live from OpenAlex

Children with disabilities often have fewer opportunities to engage in science, technology, engineering, and math programs that can enhance their educational and career opportunities. This study explored the quality, experience, and skills learned in a group-based robotics program for youth with disabilities. Survey responses of 23 youth (16 males, 7 females), aged 9 to 14 with a disability, were analyzed using descriptive statistics and thematic analysis. Our results showed that youth with disabilities who participated in a robotics program rated the quality of their experience, perceived impact of the program, and skills gained highly across most items. Children enjoyed participating in the program and especially building the robots and making friends. Clinicians should consider engaging children with disabilities in robotics programs to enhance their participation and skill development.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.508
GPT teacher head0.525
Teacher spread0.017 · 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 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

Citations19
Published2019
Admission routes1
Has abstractyes

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