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Record W4320512640 · doi:10.2991/978-2-494069-89-3_14

Research on the construction of general education system of higher education aiming at the cultivation of core literacy

2022· book-chapter· en· W4320512640 on OpenAlexaff
Actie Huang, Yiran Liang, Wei Xia, Angting Xiao

Bibliographic record

VenueAdvances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research · 2022
Typebook-chapter
Languageen
FieldComputer Science
TopicHigher Education and Teaching Methods
Canadian institutionsYork University
Fundersnot available
KeywordsCore (optical fiber)LiteracyMathematics educationEngineeringPedagogySociologyComputer sciencePsychologyTelecommunications

Abstract

fetched live from OpenAlex

Under the influence of pragmatic thinking, it is very common to emphasize subject teaching in the current college curriculum.The continuation of this situation has not further reduced the employment pressure.In order to broaden the development space of college students, scholars have turned their attention to general education.How to combine general education with university learning has become a problem.Core literacy has accumulated many years of research results, and general education aiming at core literacy has become a breakthrough in integration.This paper discusses the origins of core literacy, the current state of core literacy in higher education, and the current state of core literacy in general education, before proposing the development of a general education system of higher education with core literacy as the goal, including curriculum content, implementation methods, teaching content, teaching content, curriculum standards, etc.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.165
GPT teacher head0.504
Teacher spread0.338 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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