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Record W4308709567 · doi:10.24908/pceea.vi.15913

Where We Are: Understanding Instructor Perceptions of Empathy in Engineering Education

2022· article· en· W4308709567 on OpenAlexafffundvenue
Jennifer Howcraft, Kate Mercer

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2022
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsEmpathyContext (archaeology)CreativityPerceptionPsychologyEngineering educationPedagogyMedical educationEngineering ethicsSocial psychologyEngineeringEngineering managementMedicine

Abstract

fetched live from OpenAlex

Empathy is a necessary soft skill for 21st century engineers that can support engineering design, creativity, ethical skills, and collaboration. Empathy-based pedagogical research has predominantly focused on course or project-specific approaches. This paper presents instructor (n = 40) perceptions on empathy as a professional skill and as a pedagogical area captured in a survey distributed to the Faculty of Engineering, University of Waterloo. Instructors identified empathy as a moderately to extremely important professional skill but expressed a wider range of opinions on the importance of empathy-based pedagogy ranging from not at all important to extremely important. This difference in perceptions may be connected to self-identified gender, professional engineering status, and perceived connections between empathy and a wider range of graduate attributes. Future work will focus on a qualitative analysis of survey statements to better understand the broader context of instructor perceptions and developing a larger multi-institution study.

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 score0.401
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.187
Teacher spread0.179 · 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

Citations7
Published2022
Admission routes3
Has abstractyes

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