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Record W2933760459 · doi:10.5430/wje.v9n2p38

Improving Teaching Style with Dialogic Classroom Teaching Reform in a Chinese High School

2019· article· en· W2933760459 on OpenAlexvenueno aff
Xiaojin Kang, Jing Han

Bibliographic record

VenueWorld Journal of Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsnot available
Fundersnot available
KeywordsDialogicMathematics educationTeaching methodPedagogyPsychologyStyle (visual arts)Quality (philosophy)

Abstract

fetched live from OpenAlex

Lively and effective classroom instruction is an important feature of quality schools. Recently, the lead author's schoolhas launched a reform of classroom teaching methods to implement a dialogic model. The dialogic model, taking cuesfrom constructivist learning theories and Manabu Sato, expects educators to promote multiple kinds of classroomdialogue, including teacher-student dialogue, student-text dialogue, student-student dialogue, and self-reflectivedialogue. The reform efforts of the school are all-encompassing and include changes to teacher training, classroomobservation and teaching evaluation, lesson planning, classroom activities, homework, and testing. This reform ismeant to improve teaching quality, enhance the classroom environment, and bring about better critical thinkingoutcomes in the students. The following text chronicles the details of this reform in a large senior high school in aChinese metropolis, and the first attempts by teachers at the school to implement new dialogic teaching techniques.The preliminary analysis finds evidence of positive effects on student engagement, confidence, and motivation usingdialogic teaching techniques.

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 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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.014
GPT teacher head0.318
Teacher spread0.305 · 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 teacher head, 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

Citations4
Published2019
Admission routes1
Has abstractyes

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