MétaCan
Menu
Back to cohort
Record W4392946496 · doi:10.3991/ijep.v14i2.42341

Investigating Canadian Engineering Students’ Perceptions of Graduate Attributes: Frequency, Criticality, and Relative Importance

2024· article· en· W4392946496 on OpenAlexafffundabout
Renato Rodrigues, Jillian Seniuk Cicek, Marnie Jamieson, Sylvie Doré

Bibliographic record

VenueInternational Journal of Engineering Pedagogy (iJEP) · 2024
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsÉcole de Technologie SupérieureUniversity of AlbertaUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAccreditationEngineering educationGraduation (instrument)PerceptionCurriculumTeamworkCDIOCapstonePsychologyDescriptive statisticsMedical educationEngineeringEngineering managementComputer sciencePedagogyMathematicsMedicineMechanical engineeringManagement

Abstract

fetched live from OpenAlex

This study investigates the perceptions of Canadian engineering students regarding the frequency and criticality of the 12 graduate attributes (knowledge, skills, values, and behaviors that engineering students are expected to demonstrate upon graduation) outlined by the Canadian Engineering Accreditation Board (CEAB). This study aims to assist engineering educators in gaining a better understanding of students’ expectations regarding how engineering competencies will be demonstrated in practice. This information can guide the improvement of engineering curricula and help engineering programs meet accreditation requirements for continuous enhancement. Descriptive and test statistics were used to analyze a quantitative survey administered to 340 undergraduate engineering students at a large Canadian university. Findings suggest that the students perceived the frequency and criticality of most graduate attributes differently. Individual and teamwork, communication, professionalism, lifelong learning and engineering tools, were viewed as more frequent than critical, while ethics and equity, impact of engineering, investigation, and design were perceived as more critical than frequent. The study also found that communication, individual and teamwork, and problem analysis were perceived as the graduate attributes with the highest relative importance (frequency multiplied by criticality), which is consistent with the literature.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.322
Teacher spread0.296 · 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 designObservational
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
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Engineering Pedagogy (iJEP)Same topicEngineering Education and Curriculum DevelopmentFrench-language works237,207