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Record W2942555118 · doi:10.5539/ies.v12n5p120

Assessing the Knowledge Level of Teachers of Children with Autism Spectrum Disorder about the Importance of Applied Behavior Analysis (ABA) Strategies in Zarka City

2019· article· en· W2942555118 on OpenAlexvenueno aff
Yasser F. Khaleel

Bibliographic record

VenueInternational Education Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
Fundersnot available
KeywordsAutism spectrum disorderPsychologyAutismDevelopmental psychologyScale (ratio)Knowledge levelClinical psychologyMathematics education

Abstract

fetched live from OpenAlex

The current study aimed at assessing the knowledge level of teachers of children with Autism Spectrum Disorder about the Importance of Applied Behavior Analysis (ABA) strategies in Zarka City. Furthermore, the study attempted to explore whether teachers’ knowledge level differ according to their gender, years of experience, level of education, or specialized training. The sample of this study comprised of (60) teachers (25 male and 35 female). In order to achieve the goals of this study, the researcher constructed a questionnaire. The final version of it consisted of (27) items. The results showed that teachers of children with Autism Spectrum Disorder were given a high degree of importance on the whole scale. The mean was (2.95). The results also indicated no statistically significant differences in total degrees of importance of (ABA) strategies can be attributed to gender or level of education, while there were statistically significant differences in total degrees of importance of (ABA) strategies can be attributed to training. Finally, the results indicated statistically significant differences in total degrees of importance and no statistically significant differences in total degrees of use of (ABA) strategies can be attributed to years of experience.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.597

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 communication0.0000.000
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 head0.070
GPT teacher head0.413
Teacher spread0.342 · 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 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

Citations15
Published2019
Admission routes1
Has abstractyes

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