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Record W4401135161 · doi:10.5430/wjel.v14n6p315

The Impact of Flipped Classroom Instructional Strategy on 7th Grade Students Reading Comprehension in Jordan: An Empirical Study

2024· article· en· W4401135161 on OpenAlexvenueno aff
Shaima Mokhemer Yahya, Sara Mohammad El-Freihat, Hussein Ali Mohammed Alwama, Rima Asaad Abdul Jawad Abu Omar

Bibliographic record

VenueWorld Journal of English Language · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsReading comprehensionMathematics educationReading (process)Significant differenceFlipped classroomComprehensionComputer scienceControl (management)Quasi-experimentPsychologyMathematicsMedicinePopulationStatisticsArtificial intelligenceLinguistics

Abstract

fetched live from OpenAlex

The current study investigated the impact of flipped classroom instructional strategy on 7th grade student's reading comprehension in Jordan. A semi-experimental pre-posttest design was used through a sample consisting of (43) female students from the 7th grade selected purposefully. These were randomly assigned into two groups, the experimental group consisted of (23) female students and the control group consisted of (20) female students. The experimental groups were taught through the Flipped Classroom strategy, whereas the control group was taught according to the guidelines and procedures of teaching reading from the teacher's book. The study's results revealed a statistically significant difference between the means scores of students of the experimental and control groups and reading comprehension posttest in favor of the experimental group taught using a flipped classroom. This study may help language students capitalize on simple and interesting technology such as CDs, DVDs, Electronic platforms, and interactive applications for presenting educational materials.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.054
GPT teacher head0.462
Teacher spread0.408 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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