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Record W2902875032 · doi:10.18063/peee.v1i2.888

Study of Essential Norms and Standards for Electrical and Electronical Experiment Teaching

2018· article· en· W2902875032 on OpenAlexaff
Rajesh Kumar

Bibliographic record

VenueProgress of Electrical and Electronic Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsResearch Canada
Fundersnot available
KeywordsQuality (philosophy)Engineering managementEngineering ethicsPsychologyMedical educationComputer scienceEngineeringMedicine

Abstract

fetched live from OpenAlex

To realize the teaching goals in cultivating students’ability of conducting self-study,freely implementing of knowl- edge,developing scientific research skills,establishing team collaborative spirit,nurturing the innovative capacity and comprehensive quality,four universities led by Southeast University have conducted joint survey and design. Finally,we formulate the essential experi- ment teaching norms and standards regarding the required knowledge for experiment,experiment skills,technical methods for experi- ment,practice capacity and comprehensive qualification. The norms and standards have proven to generate fruitful and positive effects on experiment teaching.

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)0.148
metaresearch head score (Gemma)0.334
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 score0.148
Threshold uncertainty score0.781

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1480.334
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.006
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.261
Teacher spread0.257 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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