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Record W3082409740 · doi:10.5539/ies.v13n9p66

The Effectiveness of Flipped Classroom Approach on Students’ Achievement in English Language in Saudi Arabian Southern Border Schools

2020· article· en· W3082409740 on OpenAlexvenueno aff
Ali Hassan Najmi

Bibliographic record

VenueInternational Education Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsFlipped classroomMathematics educationPerceptionAcademic achievementClass (philosophy)Blended learningTest (biology)PsychologyTeaching methodPedagogyEducational technologyComputer science

Abstract

fetched live from OpenAlex

The multi-shift schooling system was adopted in Saudi Arabian southern borders schools as a result of the Arab coalition efforts to end the coup and restore the state institutions in Yemen. This has left the education community with the perception of inadequate learning time and the possible of creation of learning deficits for all students involved. Using the flipped classroom approach, this study explores this perception of learning and educational gaps resulting from the reduction of the class time and the school day. This study was executed in 2018 and used a quasi-experimental approach to explore the impact of the flipped classroom approach on students’ academic achievement in English language. A pre and post test was utilized to obtain the data. The result revealed that students taught in a flipped classroom approach achieved higher than their counterpart peers taught in the traditional approach. The study recommended the use of the flipped classrooms approach in hazardous areas or areas where there is a need to adopt multi-shift schooling system.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.059
GPT teacher head0.458
Teacher spread0.399 · 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

Citations10
Published2020
Admission routes1
Has abstractyes

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