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Record W1902972408 · doi:10.24908/pceea.v0i0.3922

ENGG 113 COMMUNICATIONS AND DESIGN: A FIRST YEAR ENGINEERING COURSE AT THE UNIVERSITY OF REGINA

2011· article· en· W1902972408 on OpenAlexaffvenue
R.J. Palmer

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPresentation (obstetrics)Class (philosophy)Course (navigation)Process (computing)CurriculumEngineering design processComputer scienceSentenceVariety (cybernetics)Mathematics educationEngineering managementMultimediaEngineeringPedagogyPsychologyArtificial intelligenceMechanical engineering

Abstract

fetched live from OpenAlex

Circa 1990 the Engineering curriculum at the University of Regina was completely overhauled. Previous to this, there were small courses in communication and design. The short courses were combined into a single standard length course of 3 credit hours, ENGG 113, Communications and Design. The underlying principle was that communication was indeed a design process. An essay must be designed, a presentation must be designed and even a sentence must be created using the fundamentals of the design process. The course incorporates unorthodox practices but it covers a variety of topics that support the design process. For example, time management is not only covered, it is practiced in class by having a student moderate each class. The class is broken into four 17 minute periods, each starting with students doing random self introductions, and ending with student summaries. Student design groups do a presentation during one of these modules. The entire class is under the control of the moderator. The lab is broken into three sections, a writing activity, a computer activity and a design activity. A design is done, and is presented at the end of the course as a WEB document. This paper describes the topics, the objectives and the methodology of the course and gives an analysis as to what works and what remains lacking.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.588

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 studies0.0000.000
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 head0.018
GPT teacher head0.191
Teacher spread0.173 · 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 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

Citations0
Published2011
Admission routes2
Has abstractyes

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