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Record W2004021612 · doi:10.5539/ass.v11n9p346

Differentiation Practices among the English Teachers at PERMATApintar National Gifted and Talented Center

2015· article· en· W2004021612 on OpenAlexvenueno aff
Mohd Hasrul Kamarulzaman, Hazita Azman, Azizah Mohd Zahidi

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDifferentiated instructionMathematics educationPsychologyEnglish languagePedagogyGifted education

Abstract

fetched live from OpenAlex

PERMATApintar National Gifted and Talented Center is Malaysia’s very own school for Malaysian gifted andtalented students, established since 2011. The center provides differentiated teaching and learning across allacademic subjects that require teachers to modify lessons according to learners’ learning preferences. However,initial implementation of differentiation raised challenges faced by the teachers. Specifically, this study exploredthe practice of differentiation in ESL classroom among the English teachers at PERMATApintar and its effectson the English language learning of Malaysian gifted and talented students. Three English teachers participatedin this qualitative study exploring their experience in providing differentiated lessons for the gifted and talentedstudents. This study found out the English language performance of the gifted and talented students was not asexpected even though differentiated ESL lessons were provided. This study also revealed that English teachersfaced challenges in preparing and implementing differentiated teaching and learning, and that a guideline forpreparing a differentiated lesson for ESL classroom is needed for a better implementation of differentiatedteaching and learning among the gifted and talented students. Further studies should investigate the moreappropriate differentiated classroom strategies in the teaching of English language that suit the Malaysian giftedand talented students, and develop a differentiation procedure especially for the gifted and talented students inMalaysia.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.999

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 studies0.0020.002
Scholarly communication0.0000.001
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 head0.043
GPT teacher head0.352
Teacher spread0.309 · 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.

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

Citations5
Published2015
Admission routes1
Has abstractyes

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