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Record W4404899543 · doi:10.23977/aetp.2024.080627

Development of a Teaching Case Library for Modern Testing Techniques and Applications Targeted at Professional Degree Graduate Students

2024· article· en· W4404899543 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Methods and Technologies
Canadian institutionsnot available
FundersQilu University of Technology
KeywordsDegree (music)Computer scienceMedical educationProfessional degreeProfessional developmentGraduate degreeMathematics educationPsychologyMedicinePhysics

Abstract

fetched live from OpenAlex

To address the limitations in the teaching cases of the "Modern Testing Techniques and Applications" course, which often focus on isolated knowledge points and outdated application contexts, this paper develops a comprehensive case library. The library compiles cases from the forefront of engineering testing research, industrial production practices, and the research outcomes of project team members. It is tailored for graduate students in mechanical engineering, integrating practical engineering applications, cutting-edge academic research, and broad content coverage. Furthermore, this paper examines the implementation process, teaching format, and key features of case-based instruction. Through this approach, students can gain insights into the latest advancements in the field, engage with real-world industrial practices, and enhance their engineering skills and innovation capabilities.

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.

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 score0.620
Threshold uncertainty score0.383

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 science0.0000.000
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 head0.112
GPT teacher head0.508
Teacher spread0.396 · 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