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Record W4390650983 · doi:10.23977/aetp.2023.071814

Research on the integrated practical teaching of ideological and political courses in large, medium and small schools

2023· article· en· W4390650983 on OpenAlexvenueno aff
Ji Juanjuan

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIdeological and Political Education
Canadian institutionsnot available
FundersGovernment of Jiangsu Province
KeywordsIdeologyPoliticsMathematics educationSociologyMedium of instructionPolitical sciencePedagogyPsychologyLaw

Abstract

fetched live from OpenAlex

The integration of ideological and political teaching in universities, middle schools and primary schools is of great significance for collaboratively leveraging the resource advantages of each school stage, building consensus on education in universities and primary and secondary schools, and strengthening the effect of moral education. The situation of ideological and political work in colleges and universities in the new era is complex. It is necessary to focus on integration, continue the ideological and political teaching achievements of primary and secondary schools, grasp the positioning and responsibilities of colleges and universities, and form a problem-oriented practical teaching that integrates teaching, research, learning, and application model. It analyzed the cognitive patterns and thinking styles of college students, grasp their existing problems in values, mental health, ideals and beliefs, etc., and propose forward-looking and effective practical teaching strategies based on this, aiming to expand the dimension and depth of education, so that the ideological quality of college students has been improved in all aspects.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.104
GPT teacher head0.539
Teacher spread0.435 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes1
Has abstractyes

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