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Record W2981811846 · doi:10.21083/ajote.v8i0.5209

Effect of Student Teams Achievement Division and Think-Pair-Share on Students' Achievement in Reading Comprehension

2019· article· en· W2981811846 on OpenAlexvenueno aff
Eucharia Okwudilichukwu Ugwu

Bibliographic record

VenueAfrican Journal of Teacher Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsStudent achievementMathematics educationReading comprehensionReading (process)PsychologyDivision (mathematics)Academic achievementComprehensionPedagogyComputer scienceLinguisticsMathematicsArithmeticPhilosophy

Abstract

fetched live from OpenAlex

AbstractThe study investigated the effect of two cooperative learning strategies, Student Teams-Achievement Divisions (STAD) and Think-Pair-Share (TPS) on senior secondary school students’ achievement in reading comprehension in Vandeikya Local Government Area, Benue State, Nigeria. A total of 78 students (43 males and 35 females), drawn from three secondary schools participated in the study. Experimental and control conditions were randomly assigned to the three intact classes: EG1 (STAD), EG2 (TPS) and CG (Control Group). The instrument used was Reading Comprehension Achievement Test (r=0.784). Data were analyzed using Mean, Standard Deviation and Analysis of Covariance (ANCOVA). The results show higher achievement gains for students in the EG1 and EG2 over those of the CG, but not across gender. The findings support the existing evidence on the efficacy of cooperative learning over the traditional teaching method. English language teachers will therefore find the two techniques useful in teaching reading comprehension. Keywords: cooperative learning, Student Teams-Achievement Divisions, Think-Pair-Share, academic achievement, reading comprehension

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)0.004
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 score0.056
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 head0.016
GPT teacher head0.365
Teacher spread0.350 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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