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Record W3088511030 · doi:10.5539/ies.v13n10p35

Effect of Curriculum Change on TIMSS Achievement in Bahrain

2020· article· en· W3088511030 on OpenAlexvenueno aff
Masooma Ali Al Mutawah, Ruby Thomas, Yazan Alghazo, Maha Al Anezi

Bibliographic record

VenueInternational Education Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMathematics Education and Teaching Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationCurriculumAcademic achievementAchievement testNumeracyPsychologyChristian ministryAffect (linguistics)PedagogyStandardized testPolitical science

Abstract

fetched live from OpenAlex

The Trends in International Mathematics and Science Study (TIMSS) is one of the most influential assessments of student achievement conducted at regular interval every four years. It provides reliable data about the mathematics and science achievement of students in grade 4 and grade 8, as well as data that informs instruction, curriculum development and teaching-learning process. Curriculum related factors are among the most prominent elements that affect TIMSS results. This study explores the impact of recent revisions in the school mathematics curriculum implemented by the Ministry of Education in Bahrain (The Bahrain Numeracy Strategy) on the TIMSS achievement results. The analysis focuses on the three cognitive domains (Knowing, Applying & Reasoning) as well as the three content domains (Number, Geometric Shapes and Measurement & Data Analysis) among fourth grade students. A thorough review of the curriculum and structured interviews and reflections with in-service teachers who witnessed a prominent change in the outcome revealed that Bahraini students’ scores improved in all three content domains while comparing 2011 and 2015. The possible explanations and reasons for those changes in achievement are further discussed.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.118
GPT teacher head0.489
Teacher spread0.372 · 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 designNot applicable
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

Citations2
Published2020
Admission routes1
Has abstractyes

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