MétaCan
Menu
Back to cohort
Record W2910162673 · doi:10.24908/pceea.v0i0.12990

Preliminary Results of a Study Assessing Engineering Students' Formation of Identity as Rhetorician

2018· article· en· W2910162673 on OpenAlexaffvenueabout
Debora Rolfes, Corey Owen, Julie Hunchak

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIdentity (music)Mathematics educationRhetorical questionCriticismPsychologyPedagogyLinguisticsAestheticsPhilosophyLiteratureArt

Abstract

fetched live from OpenAlex

The difficulty of teaching communicationskills to engineering students in a way that facilitates thetransfer of knowledge to workplace situations is widelyacknowledged. At the College of Engineering at theUniversity of Saskatchewan we have tried to address thisdifficulty by developing a programme that attempts to addthe identity of effective communicator to the students’identity as engineer. The purpose of this study is to beginto assess whether students are forming this identity. UsingBurke’s concept of terministic screens and the analyticaltools of cluster criticism, we analyze the transcripts ofinterviews of students returning from internshipexperiences to assess whether students’ language choicesreflect a rhetorical orientation to the world and thus thedevelopment of an identity of rhetorician

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)0.015
metaresearch head score (Gemma)0.049
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 score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0040.004
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.012
GPT teacher head0.271
Teacher spread0.259 · 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

Citations2
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueProceedings of the Canadian Engineering Education Association (CEEA)Same topicDiscourse Analysis in Language StudiesFrench-language works237,207