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Record W2900267706 · doi:10.5539/elt.v11n12p38

An Investigation Report of the Status Quo and Training Demands of Rural Primary English Teachers in North Anhui Province

2018· article· en· W2900267706 on OpenAlexvenueno aff
Guangcun Zhao

Bibliographic record

VenueEnglish Language Teaching · 2018
Typearticle
Languageen
FieldComputer Science
TopicHigher Education and Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsStatus quoWorkloadPsychologyCompetence (human resources)Training (meteorology)Mathematics educationMedical educationPedagogyHigher educationRural areaPolitical scienceManagementMedicine

Abstract

fetched live from OpenAlex

Through questionnaires and statistical analysis, it is found that the status quo and training needs of rural primary English teachers in northern Anhui Province are as follows: (1) Teachers are young, female and hold concurrent posts in English teaching; (2) Most teachers have a strong desire to participate in the training, but fail to do so due to heavy workload of the course, or lack of the opportunity to go out to participate in higher level training; (3) Their ideal trainers are excellent front-line English teachers, and eager to get trained in education concepts, teaching skills and technology, and teaching modes. They are not interested in the study of education theory or academic research; (4) Many teachers lack confidence in their competence and urgently need training in their basic skills. In view of the above results, countermeasures are put forward as follows: to speed up the transformation of teachers’ growth, strengthening teachers’ basic skills of teaching, teaching while conducting scientific research, and combining field training and remote training together.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.286
Teacher spread0.272 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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