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Record W3002486847 · doi:10.24908/pceea.vi0.13746

TEACHING ASSISTANT TRAINING IN ENGINEERING DESIGN

2019· article· en· W3002486847 on OpenAlexafffundvenueabout
Justine Boudreau, Hanan Anis

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2019
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCornerstoneMedical educationEngineering managementQuality (philosophy)Engineering educationEngineering design processEngineeringTraining (meteorology)PsychologyMathematics educationComputer scienceMedicineMechanical engineering

Abstract

fetched live from OpenAlex

The Faculty of Engineering at the University of Ottawa is home to multiple rapid prototyping facilities and entrepreneurship spaces. These include a makerspace, a machine shop and a design space for any student to use free of charge. First- and second-year students also take courses in the Makerlab, a sister facility to the Makerspace, that introduces them to collaborative project-based learning, engineering problem-solving and prototyping in a cornerstone design course. Each three-hour weekly lab has a teaching assistant (TA), typically a graduate student, and a project manager (PM), typically an undergraduate student who has taken the course previously. They are responsible for teaching the lab content and guiding the students through their design process. Since design courses are weighted heavily toward projects and labs, this evidence-based practice paper is part of a study that has the goal of understanding, via student evaluations, the impact of TA and PM training on their performance. This paper presents an analysis of the impact of TA and PM training, based on the students’ evaluation of their TA’s and PM’s performance. Factors considered were the amount of training received by the TAs and PMs, the type of training and the satisfaction of the students. The students were surveyed to gauge their satisfaction with the quality of their TAs and PMs, and the survey results were compared with a number of outcomes.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.006
GPT teacher head0.183
Teacher spread0.177 · 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.

Study designSimulation or modeling
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

Citations1
Published2019
Admission routes4
Has abstractyes

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