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Record W4381730052 · doi:10.5430/jct.v12n3p147

A Study on College Life Experiences and Support Strategies of Students Participating in Higher Education Programs for Students with Developmental Disabilities

2023· article· en· W4381730052 on OpenAlexvenueno aff
Yung Keun Park

Bibliographic record

VenueJournal of Curriculum and Teaching · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsnot available
FundersJoongbu University
KeywordsMedical educationPsychologyCognitive disabilitiesHigher educationPerceptionCognitionQuality (philosophy)MedicinePolitical science

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the perceptions of students with developmental disabilities on higher education programs at universities and to suggest the strategies to improve the quality of their college life experiences. For the purpose of this study, survey were implemented for students participating in the higher education program for people with developmental disabilities. Survey was conducted by distributing the questionnaire through mail, e-mail, and direct visits. In the research results, the future vision of students who want to achieve through participation in higher education programs was presented, and the results of analysis of academic characteristics and motivation, academic cognitive characteristics, social responsibility and leadership characteristics of students participating in higher education programs were presented. Through the results of this study, it will not only be possible to improve the quality of higher education programs that students with developmental disabilities can participate in, but also to improve their quality of life through the provision of appropriate programs.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.074
GPT teacher head0.442
Teacher spread0.368 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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