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Record W4389641425 · doi:10.23977/aetp.2023.071708

A Case Study on the Teaching Design of the High School Art Appreciation Course What is a Work of Art Based on the Core Competence of Art

2023· article· en· W4389641425 on OpenAlexvenueno aff
Junling Zhou, Huiling Zhang, Zichuan Liu

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2023
Typearticle
Languageen
FieldComputer Science
TopicDigital Media and Visual Art
Canadian institutionsnot available
FundersNational Ethnic Affairs Commission of the People's Republic of ChinaChina Scholarship Council
KeywordsArt methodologyCompetence (human resources)Visual arts educationPaintingArt criticismWork of artArt designMathematics educationVisual artsContemporary artAestheticsPsychologyArtThe artsArt historyPerformance art

Abstract

fetched live from OpenAlex

Appreciation of art works is an essential part of art appreciation course, the essence of which is to discover the hidden connotations and the meaning behind them by appreciating the visual representation of the work. Thus, incorporating the teaching design of the core competence of art into the art course is conductive to better solving the problem of single, scattered, and monotonous subject knowledge. This paper takes the high school art appreciation course What is a Work of Art as an example, analyzes high school art appreciation courses from the perspective of core competence, the Xiangmei version of high school art textbooks, comparison of teaching designs of different teaching cases, as well as optimization plans based on core competence, and thoroughly explores the significance of art work. The purpose is to help students establish a big concept of art work, understand the meaning of different types of art works, find beautiful things in life, develop their interest and love for painting studying, and understand the meaning of art appreciation.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.045
GPT teacher head0.372
Teacher spread0.328 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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