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Record W1856317910 · doi:10.1108/jat-10-2014-0030

The iPad as a mobile assistive technology device

2015· article· en· W1856317910 on OpenAlexaff
Linda Chmiliar, Carrie Anton

Bibliographic record

VenueJournal of Assistive Technologies · 2015
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsAthabasca University
Fundersnot available
KeywordsViewpointsAssistive technologyTerminologySet (abstract data type)Mobile deviceMultimediaComputer scienceField (mathematics)PsychologyMathematics educationHuman–computer interactionWorld Wide Web

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to present the viewpoint of the authors on the use of the iPad as an assistive technology tool for post-secondary students with disabilities. Design/methodology/approach – Although this paper is not classified as a research article, the viewpoints discussed by the authors are related to a pilot study and continuing case study research they are conducting. Findings – The authors indicate that they have been surprised at the positive results they have observed in the iPad implementation, particularly with students moving to the iPad to continue their studies at the completion of the research. Practical implications – This paper discusses the opportunities and limitations afforded by the use of the iPad with post-secondary students as well as suggestions for implementation. Social implications – After decades of experience in the field of assistive technology, the authors are becoming convinced that the iPad offers significant opportunities for learning for students with disabilities. One of the exciting parts of being involved in these iPad studies has been to observe: the transformation of student study skills, the increased student self-discovery around how they learn, and the increase in student confidence in technology use. Perhaps rather than labeling the iPad as a mobile device or an assistive technology tool, the authors need to look at different terminology to define it. The ownership of this device by post-secondary students is growing every year, and it is a device that does not set students with disabilities apart from their peers. It is a device that can effectively support student learning through built in accessibility features and the use of commonly available and used apps. Perhaps using the term “equalizing technology” to describe the iPad might be more appropriate. Originality/value – This paper discusses the opportunities and limitations afforded by the use of the iPad with post-secondary students as well as suggestions for implementation. This is a rapidly developing area in universities and colleges around the world.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.005

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 head0.099
GPT teacher head0.456
Teacher spread0.357 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2015
Admission routes1
Has abstractyes

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