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Record W2960328164 · doi:10.5539/hes.v9n3p65

The Implementation of the Lesson Study in Basic Teacher Education: A Research Review

2019· review· en· W2960328164 on OpenAlexvenueno aff
Eurydice-Maria Kanellopoulou, Μαρία Δάρρα

Bibliographic record

VenueHigher Education Studies · 2019
Typereview
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsLesson studyLesson planMathematics educationClass (philosophy)Teacher educationPedagogyPsychologyEmpirical researchTeaching methodPlan (archaeology)Higher educationProfessional developmentPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The lesson study is a teaching practice that was first applied to the educational system of Japan. It is a form of classroom research in which teachers cooperatively plan, teach, observe and share the results in a class lesson. The purpose of this study is to review the effectiveness of the implementation of the lesson study in basic teacher education through the review of 29 empirical researches conducted both in Greece and the world over the past decade (2008-2018). In particular, a. the contribution of the lesson study in mobilizing and improving the performance of preservice teachers and b. the attitudes and beliefs of preservice teachers and their educators on the use of this particular teaching approach. The results of the research revealed that lesson study contributes to mobilizing preservice teachers, improving their performance, and developing positive attitudes and beliefs of learners and trainers regarding its use in higher education. There is also a need for further research on the implementation of the lesson study in higher education, mainly in Greece, compared to the international field.

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)0.006
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.007
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.671
GPT teacher head0.663
Teacher spread0.008 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2019
Admission routes1
Has abstractyes

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