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Record W1542951891

Perception of English Beginning Teachers in Middle Schools About Teaching Competencies

2015· article· en· W1542951891 on OpenAlexvenueno aff
Jie Xu

Bibliographic record

VenueCanadian social science · 2015
Typearticle
Languageen
FieldComputer Science
TopicHigher Education and Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic shortagePerceptionMathematics educationClass (philosophy)Subject matterPsychologyTeaching methodPedagogyReflection (computer programming)Computer scienceCurriculum
DOInot available

Abstract

fetched live from OpenAlex

This paper is trying to make an effort to get a glimpse of English beginning teachers’ perception about teaching competencies. 142 beginning teachers from 70 middle schools in 8 cities in Guangdong Province were taken as the samples. They were asked to rank the items of teaching competencies about the importance and the lack of the competencies. As a result, the top five important teaching competencies are English pedagogical knowledge, Class management skills, Doing teaching reflection, Choosing and utilizing proper teaching methods and techniques and Knowledge of subject matter. Meanwhile, participants believed the five items including Class management skills, Choosing and utilizing proper teaching methods and techniques, Doing teaching reflection, Assessing teaching and learning and Having knowledge of students’ learning situation are what they need most to improve. As for field dimension, English language comprehensive competencies are considered as the most important ones for beginning teachers; when it comes to the shortage, Assessment and evaluation is rated in the first place, which means beginning teachers are most lacking in.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.379
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.322
Teacher spread0.270 · 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
Published2015
Admission routes1
Has abstractyes

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