MétaCan
Menu
Back to cohort
Record W1950680748 · doi:10.24908/pceea.v0i0.3621

Changing Geers: Engineering Instructor Perspectives on Education

2011· article· en· W1950680748 on OpenAlexaffvenue
Andrew Roncin

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsRed River College
Fundersnot available
KeywordsDiversity (politics)Context (archaeology)Engineering educationBloom's taxonomyPsychologyCognitionEngineering ethicsPedagogyMathematics educationKnowledge managementEngineeringComputer scienceEngineering managementSociology

Abstract

fetched live from OpenAlex

This paper is based on the qualitative research work done on instructor perspectives about teaching1. The diversity of answers in interpreting what a professional engineer is.2. The different ways in which we connect theory and application in our classrooms.3. How instructor expectations change along with student abilities. These findings are examined in the context of bloom’s revised taxonomy. To consider how the knowledge, cognitive are supported in engineering. From this, recommendations about using open ended (engineering) problems to develop student’s engineering. The purpose of which is to better understand the attitudes and motivations of instructor’s so that when changes are recommended to accommodate CEAB requirements they are both appropriate and meaningful. The paper briefly highlights the context and methodology of the research. But of interest to engineers and educators are the following three findings. confidence and abilities are considered.

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)0.011
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.009
Scholarly communication0.0080.008
Open science0.0010.007
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.005
GPT teacher head0.171
Teacher spread0.166 · 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 designQualitative
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

Explore more

Same venueProceedings of the Canadian Engineering Education Association (CEEA)Same topicEngineering Education and Curriculum DevelopmentFrench-language works237,207