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Record W4406313549 · doi:10.21083/ajote.v13i2.8024

Using Lesson Study as a tool to cope with instructional challenges: A case study of Chemistry teachers in Nigeria

2024· article· en· W4406313549 on OpenAlexvenueno aff
Monday Moju, Olusegun Fashakin

Bibliographic record

VenueAfrican Journal of Teacher Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumLesson studyMathematics educationProfessional developmentProcess (computing)Lesson planTeaching methodPedagogyFace (sociological concept)PsychologyMedical educationChemistryMedicineComputer scienceSociology

Abstract

fetched live from OpenAlex

Educators encounter many obstacles in effectively planning and teaching students in the classroom. One of the most significant challenges is the constraints imposed by curriculum standards, which can hinder teachers from customizing lesson plans that reflect students' current situations. To address this issue, a research study was conducted to investigate how collaborative professional development using lesson study could support teachers in managing lesson planning and teaching issues in schools. Two chemistry teachers in Educational District IV Lagos State, Nigeria, participated in the lesson study process, were interviewed, and engaged in writing a reflection. The data gathered were transcribed, coded, analyzed, and the results revealed that chemistry teachers face difficulties due to curriculum standards and expectations of national and external examinations. Nevertheless, through lesson study, the teachers recognized the necessity of prioritizing students' needs while designing lesson plans to overcome challenges and make chemistry relevant to students.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0030.003
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 head0.097
GPT teacher head0.445
Teacher spread0.348 · 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 designQualitative
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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