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Record W2169686001 · doi:10.5206/eei.v18i2.7625

Assistive Technology as an Accommodationfor a Student with Mild Disabilities: The Case of Alex

2008· article· en· W2169686001 on OpenAlexaffvenueabout
Darlene Brackenreed

Bibliographic record

VenueExceptionality Education International · 2008
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsNipissing University
Fundersnot available
KeywordsPsychologyLearning disabilityStudent achievementPsychological interventionAssistive technologyMedical educationAcademic achievementMathematics educationStudent teacherSpecial educationPerceptionPedagogyTeacher educationDevelopmental psychologyMedicineComputer science

Abstract

fetched live from OpenAlex

This case study investigated the impact of selected types of adaptive and assistive technology (AT) on the learning gains and academic achievement levels of a fe-male student with mild disabilities in her sixth and seventh grades in a Catholic school board in northeastern Ontario. Interviews were conducted with the parent, student, and pre-service teachers. Records from 6 school years were examined to determine the student’s academic history and performance levels, and reports from numerous professionals involved in the assessments and interventions of the student were explored. Reports from the community service-learning assignment provided information regarding teaching approaches and student responses. A synthesis of all data suggested that AT had resulted in increased student achieve-ment levels, perceptions of capability, and student self-advocacy. Additionally, the acceptance and use of AT by teachers increased significantly with the training of their student and the student’s subsequent tutoring of the teacher and classmates in the use of selected assistive 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.000

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 head0.068
GPT teacher head0.447
Teacher spread0.379 · 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

Citations9
Published2008
Admission routes3
Has abstractyes

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