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A Seminar for Real‐time Interactive Simulation of Engineering Projects: An Innovative Use of Video‐conferencing and IT‐based Educational Tools

2002· article· en· W1971852361 on OpenAlexaff
Mario Bourgault, DENIS LAGACEA

Bibliographic record

VenueJournal of Engineering Education · 2002
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversité du Québec à Trois-RivièresNatural Sciences and Engineering Research Council of CanadaPolytechnique Montréal
Fundersnot available
KeywordsContext (archaeology)VideoconferencingWork (physics)Engineering managementGraduate studentsEngineering educationDistance educationTeleconferenceEngineeringComputer scienceMultimediaPedagogy

Abstract

fetched live from OpenAlex

Abstract Graduate‐level programs in project management continue to attract many engineers looking for tools and methods to help them deal with the complexity of their activities. In order to meet this demand, many universities are experimenting with new teaching methods, based on information and communications technologies. This article presents a teaching approach which consists in recreating the organizational context in which engineers generally have to manage their projects. In practical terms, it is a full‐day seminar that involves simulating a project from its launch until product delivery. Like most real projects, the activity takes place at more than one location simultaneously and relies on the intensive use of communications technologies, including video‐conferencing, to coordinate the work teams. Although the primary client base is graduate students, this method is just as relevant for professional engineers and undergraduate students. Over 400 participants have taken part in this seminar to date.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.032
GPT teacher head0.272
Teacher spread0.240 · 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 designNot applicable
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

Citations11
Published2002
Admission routes1
Has abstractyes

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