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Record W4321786188 · doi:10.5430/jct.v12n1p288

The Contribution of the Flipped Classroom to the Optimization of Alternating Teaching in Morocco

2023· article· en· W4321786188 on OpenAlexvenueno aff
Mohammed Ben Mesaoud, Saïd Boubih, Khalid Najoui, Mohammed Rabih Raissouni, Essadiq Assimi, Hicham El Kazdouh, Mohamed Radid

Bibliographic record

VenueJournal of Curriculum and Teaching · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsFlipped classroomMathematics educationClass (philosophy)Context (archaeology)Test (biology)PsychologyCognitionQuasi-experimentPedagogyComputer scienceSociologyGeographyBiology

Abstract

fetched live from OpenAlex

This research aims to conduct an experimental study to apply a model of flipped classroom pedagogy (FCP) in selected Moroccan classrooms. This is to study its effectiveness in the local context, and to explore the possibility of investing the opportunities it offers to manage and optimize Alternating Teaching (AT), which was adopted during the Covid-19 pandemic to ensure educational continuity. This study adopted a semi-experimental design with a pre- and post-test, and utilized two groups (experimental and control) to evaluate the impact of FCP on AT performance. The study involved 67 students from two secondary school classes, 33 students in the Life and Earth Sciences (LES) class and 34 students in the Physics and Chemistry (PC) class. The results were analyzed using the t-test and learning gain as a function of cognitive abilities and confirmed the effectiveness of FCP in enhancing AT performance. These findings were further supported by classroom observations and semi-structured interviews with students in the experimental group, which showed the positive impact of FCP on both the didactic and relational aspects of AT.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.019
GPT teacher head0.361
Teacher spread0.342 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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