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Record W4386800546 · doi:10.23977/aetp.2023.071003

Common Mistakes and Countermeasures of Using Learning Material in the Project-Driven Applicational Technology Courses—Taking the Teaching of Air Conditioning Course as an Example

2023· article· en· W4386800546 on OpenAlexvenueno aff
Shidong Li

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2023
Typearticle
Languageen
FieldComputer Science
TopicHigher Education and Teaching Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumProject-based learningProcess (computing)Computer scienceMathematics educationTeaching methodCourse (navigation)Order (exchange)Engineering managementEngineering ethicsPedagogySociologyPsychologyEngineering

Abstract

fetched live from OpenAlex

Project-driven teaching is an improvement of traditional teaching method based on knowledge-driven system. It emphasizes that the teaching process is driven by the implementation of the project, rather than based on traditional textbooks. Therefore, there are some disputes about how the textbook should play its role correctly in the project-based teaching. In the process of implementing project-based teaching, some views hold that since it is driven by project, it is nature to abandon the traditional textbooks; others, on the other-hand, continue to organize teaching only or at least mainly based on textbooks. The third part of people think that the project-based curriculum must have special Project-based Curriculum textbooks, so the textbook should be written as an operation manual according to the project order. The author makes a detailed analysis of the three views on the use of textbook in the project-based curriculum, and then puts forward my own views.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.053
GPT teacher head0.442
Teacher spread0.389 · 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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