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Record W4313055541 · doi:10.23977/aetp.2022.061203

A Study on the Significance of UDL-Based Teaching Practices for Students with Intellectual Disabilities

2022· article· en· W4313055541 on OpenAlexvenueno aff
Yuhang Yang, Jinjing Ma

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
FundersYunnan Normal University
KeywordsUniversal Design for LearningIntellectual disabilityMathematics educationPsychologyUniversal designSpecial educationLearning disabilityPedagogyComputer scienceDevelopmental psychology

Abstract

fetched live from OpenAlex

In recent years, the Universal Design for Learning to Support Students with Intellectual Disabilities (UDL) has been used as a methodological framework in our work with students with intellectual disabilities, providing a flexible developmental environment for integrated education and addressing the learning differences of students. It plays an important role in supporting and promoting learning in general education to all students, including students with intellectual disabilities. The concepts, implementation principles, and theoretical foundations of Universal Design for Learning are explored to reveal the practical implications of Universal Design for Learning as applied to students with intellectual disabilities.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.619
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.067
GPT teacher head0.487
Teacher spread0.421 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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