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Record W4307865599 · doi:10.5430/wjel.v12n8p371

Research on Online Classroom Language between Teachers and Students

2022· article· en· W4307865599 on OpenAlexvenueno aff
GAO JIE, Samah Ali Mohsen Mofreh, Sultan Salem

Bibliographic record

VenueWorld Journal of English Language · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCoding (social sciences)CurriculumMathematics educationClass (philosophy)Computer scienceQuality (philosophy)Atmosphere (unit)PsychologyPedagogySociology

Abstract

fetched live from OpenAlex

Under the new situation, online live teaching has become one of the important teaching methods. The verbal interaction between teachers and students is an important explicit behavior in online live teaching. To further improve the quality of teacher-student verbal interaction in an online live classroom, this study constructs a speech interaction behavior coding system for teachers and students in an online live classroom, which is based on the ITIAS teacher-student interaction coding system and Bellack’s interaction structure theory. By observing the online live class of Luoyang No.56 middle school, conclusions are found in terms of interactive structure, the level of interaction, the interactive atmosphere, and the interactive dynamics. Online Classroom Language Between Teachers and Students infulences the effectiveness of the classes greatly. According to the study, the researcher put forward some strategies to improve the effectiveness of teacher-student verbal interaction in online live classrooms. The researcher believed that this research will give important guidance for the development of the school-based online live curriculum, and promote the development of the school-based online live curriculum.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.201
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.051
GPT teacher head0.440
Teacher spread0.389 · 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 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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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