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Record W2802126802 · doi:10.3968/10272

Classroom Teaching in Non-Governmental Institutions of Higher Education in China: Characteristics, Problems and Development Strategies

2018· article· en· W2802126802 on OpenAlexvenueno aff
Gang Li, Fang Xiaotian

Bibliographic record

VenueHigher education of social science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIdeological and Political Education
Canadian institutionsnot available
Fundersnot available
KeywordsStatus quoConsciousnessChinaGovernment (linguistics)Mathematics educationPsychologyProfessional developmentQuality (philosophy)Social changeOrder (exchange)SociologyPedagogyPolitical scienceBusiness

Abstract

fetched live from OpenAlex

This paper chooses a representative sample of college C, a non-governmental college located in western China, to analyze the characteristics and problems of classroom teaching in Chinese private colleges. One of the characteristics is that the quantity of teachers is basically met, yet featured with the imbalanced structure. The problems are as follows: lack of teachers’ role consciousness, motivation for self-development, teachers’ classroom awareness, personal and professional development ability, and teachers’ training consciousness. The reasons for them are: a disparity between philosophy of schooling and teaching attitudes; insufficient investment in teachers’ quality and a vacancy on teachers professional development; restricted capacity for improvement on teaching, resulted from the incompatible content of training with the training mode, and so on. In order to change the status quo, measures should be taken through the government’s support and social advocacy, with a focus on the renewal of management, and the remolding the idea of “teaching for the people”.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.031
GPT teacher head0.364
Teacher spread0.333 · 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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