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Record W1925506615 · doi:10.24908/pceea.v0i0.5786

INDUSTRY PERCEPTIONS OF GRADUATE ATTRIBUTE REQUIREMENTS FOR THE WORKPLACE

2015· article· en· W1925506615 on OpenAlexaffvenueabout
D. S. Petkau

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAccreditationGraduation (instrument)CorporationMedical educationPerceptionProcess (computing)Service (business)PsychologyGraduate studentsEngineeringMedicineBusinessMarketingComputer science

Abstract

fetched live from OpenAlex

At the Faculty of Engineering at the University of Manitoba research has been undertaken to determine the level of student competency in the graduate attributes as set forth by the CEAB accreditation process. This study takes an alternative view and seeks to understand the current industry requirements for a new graduate employee based on the graduate attributes. It consisted of a questionnaire completed by two groups of engineers working in a major energy corporation in the Province of Manitoba. One group consisted of senior engineers with a minimum of 15 years experience while the other was of new graduates with at minimum 18 months of service. The groups were asked to complete a questionnaire on the level of competency they felt was required for new graduates entering the workplace. This paper describes the process and the analysis of the information. Results were compared with an assessment of a new graduate’s competency levels. The information shows that while a student’s competency levels at graduation may be lower than expected they still generally meet the requirements of the workplace. Information also shows that areas of concern are not in the technical areas but rather in the professional skills.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.249
Teacher spread0.219 · 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

Citations2
Published2015
Admission routes3
Has abstractyes

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