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Record W3180312667 · doi:10.24908/pceea.vi0.14903

ENGINEERING INSTRUCTORS AND THEIR TEACHING GOALS, TEACHING PRACTICES AND CONCEPTIONS OF STUDENT LEARNING IN UNDERGRADUATE EDUCATION

2021· article· en· W3180312667 on OpenAlexaffvenueabout
Lisa Romkey

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2021
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEngineering educationTeaching and learning centerDiversity (politics)Set (abstract data type)Active listeningTeaching methodMathematics educationSituatedPedagogyActive learning (machine learning)PsychologyEngineeringComputer scienceSociologyEngineering management

Abstract

fetched live from OpenAlex

This paper shares the results of a multiinstitutional study examining the teaching goals andpractices of engineering instructors. Through both a survey and a set of interviews, engineering instructors at four institutions in Ontario were invited to share their key teaching and learning goals, teaching philosophy, and the use of teaching and learning activities in the teaching of undergraduate engineering students. Engineering instructors shared a surprising diversity of teaching goals and practices, and through a discussion of powerful teaching activities, a set of conceptualizations around student learning emerged, ordered in decreasingprominence: Students learn through: (1) making realworld connections; (2) application of concepts; (3) interaction with the instructor; (4) interaction between students; (5) independence and ownership and (6) listening to what the professor says and does. These views are all reflected in the diversity of learning theories available in the literature, and in particular situated learning theory, but an understanding of these specific conceptualizations, articulated by engineering instructors, can be used to better support engineering instructors in their teaching, and in the development of new curricular initiatives in undergraduate engineering education. This work expands on the existing literature on teaching in higher education and teaching practices in engineering.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.224
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 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

Citations0
Published2021
Admission routes3
Has abstractyes

Explore more

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