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Record W4386800472 · doi:10.23977/aetp.2023.071005

The Requirements and Functions of Multimedia Teaching for Different Subjects

2023· article· en· W4386800472 on OpenAlexvenueno aff
Xinyi Tang

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2023
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsPaceMultimediaComputer scienceLeverage (statistics)Promotion (chess)CITESConstructiveInteractive mediaTeaching methodMathematics educationPsychologyProcess (computing)

Abstract

fetched live from OpenAlex

With the continuous innovation and development of technology, multimedia technology has been introduced in multiple fields of various industries to improve corresponding performance. At the same time, Education, as one of the important ways for national development, should also use auxiliary tools that follow the pace of the times and match the needs. Based on the development trend of the times and the promotion of national education policies, the field of education also cites multimedia technology to assist teaching. As a modern means, it can inject vitality into teaching, optimize teaching models, and promote the development of various subjects themselves. The use of multimedia in education has different requirements for different subjects and also has different effects. This study will analyze based on this. Firstly, explain the development history and trends of multimedia. Secondly, Divide the teaching subject into teachers, students, and schools, and discuss the requirements and roles of multimedia teaching for them separately from different dimensions. Although multimedia plays a constructive role in promoting education and teaching, there are also some problems in the use of it. Therefore, this article concludes by proposing precautions when using teaching media in teaching, and help users better leverage the role and advantages of multimedia in teaching. Hoping to provide research direction and reference value for research on using multimedia to promote education and 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 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)0.000
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 score0.184
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.037
GPT teacher head0.408
Teacher spread0.371 · 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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