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Record W3200526339 · doi:10.33137/ijidi.v5i3.36136

Assistive Technology in Education

2021· article· en· W3200526339 on OpenAlexfundno aff
Vanesa Ayon, Andrew Dillon

Bibliographic record

VenueThe International Journal of Information Diversity & Inclusion (IJIDI) · 2021
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsAssistive technologyFraming (construction)Engineering ethicsTechnology educationPsychologyPedagogyComputer scienceEngineeringHuman–computer interaction

Abstract

fetched live from OpenAlex

This article offers a socio-technical framing of assistive technology design for in-classroom use to enable a better understanding of how to improve educational opportunities and outcomes for learners with disabilities. By addressing social inequities in public education and recognizing user-centered design faults and inadequacies in the current implementation of assistive technology in the educational environment, this paper focuses on understanding the experiences of learners with disabilities. This article discusses challenges faced when adopting such technology and the effects of the current well-intentioned but flawed implementation of assistive technology. The authors highlight the limitations and shortcomings of the current approaches portrayed in previous research and educational practices. The article concludes with a call for a socio-technical approach to the adoption of assistive technology to augment the learning experience for a more inclusive atmosphere, and encourages a deeper appreciation for the interrelatedness between people, educational organizations, and technology.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.007
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.383
Teacher spread0.353 · 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 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

Citations10
Published2021
Admission routes1
Has abstractyes

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Same venueThe International Journal of Information Diversity & Inclusion (IJIDI)Same topicAssistive Technology in Communication and MobilityFrench-language works237,207