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Meta Analysis of the Impact of the Flipped Classroom on Secondary Students' Mathematics Performance

2024· book-chapter· en· W4392672501 on OpenAlex
Angeline M. Pogoy, Helen B. Boholano, Angelito Cabanilla, Lelani Dapat, Michel Plaisent

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in educational technologies and instructional design book series · 2024
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsFlipped learningFlipped classroomMathematics educationMathematicsPsychologyComputer science

Abstract

fetched live from OpenAlex

This meta-analysis assesses the effect of flipped classroom on secondary students' mathematics performance. Seven scholarly electronic databases were used to identify the papers published in English language journals on flipped classroom in secondary students' mathematics performance through Google Scholar, Scopus, Proquest, PDF Drive, core.ac.uk, archive.org, elephind.com databases published in 2013 for 2021. With the use of inclusion and exclusion criteria, 15 published research articles were included in the meta-analysis using the preferred reporting items for systematic reviews and meta-analyses (PRISMA). A publication bias showed a positive result in students' mathematics performance. No published studies had shown negative results in secondary students' mathematics performance using flipped classroom as a strategy in teaching. Using larger scope of moderating variables with balanced statistical results in utilizing flipped classroom as a strategy in math instruction may provide more insights that are evidence-informed application and teaching practice.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.291
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.371
Teacher spread0.319 · 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