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Record W2906296773 · doi:10.5539/mas.v13n1p162

Teachers’ Perceptions on Drama’s Role in Enhancing Young Learners’ Developmental Domains

2018· article· en· W2906296773 on OpenAlexvenueno aff
Sahar Yacoub Abu-Helu

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCreative Drama in Education
Canadian institutionsnot available
Fundersnot available
KeywordsDramaPracticumPsychologyPerceptionCognitionPedagogyMathematics educationVisual artsArt

Abstract

fetched live from OpenAlex

The study aimed to investigate teachers’ perceptions on drama’s role in enhancing young learners’ developmental domains. The sample consisted of (133) cooperative- teachers chosen upon availability from the collaborating schools with the Classroom Teacher and the Early Childhood Education Practicum Courses in the University of Jordan. The cooperative-teachers’ perceptions data were collected through a questionnaire designed by the researcher based on the literature review related to drama as a teaching tool. The instrument included three main domains; the social-emotional, linguistic-communicative and cognitive domain. The findings revealed that drama highly enhanced young learners’ developmental domains, in which the social-emotional domain came as the highest score according to the teachers’ perceptions. The results also revealed that both the specialization and experience variables proved not to cause any statistical significant differences on the cooperative- teachers’ perceptions about the role of drama in teaching young learners. Further studies were recommended on investigating teachers’ actual practices in applying drama in their teaching actions.

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)0.002
metaresearch head score (Gemma)0.004
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.023
GPT teacher head0.264
Teacher spread0.241 · 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
Published2018
Admission routes1
Has abstractyes

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