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Record W7055234863

Canadian Postsecondary Students with Learning Disabilities Describe Experiences with Assistive Services

2024· article· en· W7055234863 on OpenAlexaboutno aff

Bibliographic record

VenueScholarWorks (Walden University) · 2024
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPostsecondary educationLearning disabilityThematic analysisQualitative researchSpecial educationAssistive technologyHigher educationQualitative property
DOInot available

Abstract

fetched live from OpenAlex

Colleges and universities typically assist students with learning disabilities. In Canada, such programs are legally mandated to ensure equal access to educational opportunities. However, there is little in the current research literature on the experiences Canadian students with learning disabilities have with using assistive services provided by their postsecondary school, especially for students who have successfully completed postsecondary education. This generic qualitative study used the framework in disability studies in education as a foundation. The information for this study was gathered through online interviews with individuals with learning disabilities who were enrolled or had successfully completed their postsecondary education. A thematic data analysis provided clear insights into the lived experiences postsecondary students with learning disabilities have in using assistive services from their school. In general, the findings revealed that regardless of the negative experiences students with disabilities had in grade school being accommodated and recognized, they had much better experiences being accommodated in college and university. This study may contribute to positive social change by offering insights to colleges and universities to increase or improve the assistance provided to students with learning challenges. It may also motivate students with learning disabilities who may be afraid to enroll in postsecondary education, out of the fear of not being “good” enough.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.178
Teacher spread0.174 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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