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Record W3212943771 · doi:10.5539/jel.v11n1p54

Students with Special Educational Needs: Explaining Their Social Integration and Self-Concept

2021· article· en· W3212943771 on OpenAlexvenueno aff
Salwa Mostafa Khusheim

Bibliographic record

VenueJournal of Education and Learning · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsBachelorPsychologySocial integrationCurriculumSpecial needsPerceptionSocial needsQuality (philosophy)Mathematics educationLikert scaleMedical educationPedagogySociologyDevelopmental psychologyPolitical science

Abstract

fetched live from OpenAlex

Social integration of special need students is viewed as a necessary phenomenon for the skills’ development which adds quality to their lives and provides them with satisfaction. This study explores the perception and attitude of the teachers towards social integration as a general school policy. A total of 150 individuals were selected from the integrated primary schools in KSA. Survey approach was employed to collect data using a close-ended questionnaire which was then statistically analysed. The results revealed that there is a positive impact of the social integration upon the special needs students. A statistically significant difference was found among participants based on their experience, education, and age. Moreover, there was significant difference in the attitudes of participants with Diploma in Education qualifications and Bachelor in Education qualifications towards integration. The study concluded that the implementation of the integrated school as general policy should be considered and an effective teacher training curriculum with special needs courses should be introduced.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.320
Teacher spread0.305 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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