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Record W4403794128 · doi:10.24908/pceea.2023.17005

Using senior undergraduate students as coaches in an introductory chemical engineering design course

2024· article· en· W4403794128 on OpenAlexaffvenue
Roza Vaez Ghaemi, Gabriel Potvin

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2024
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCourse (navigation)Mathematics educationUndergraduate researchMedical educationPsychologyEngineering physicsEngineeringMedicine

Abstract

fetched live from OpenAlex

Senior undergraduate students were hired as Teaching Assistants (TAs) in CHBE 221, an introductory bioprocess design course offered in the Department of Chemical and Biological Engineering at University of British Columbia, and the roles were recast from traditional course support, to being coaches and mentors to a small number of teams working on term-spanning design projects. This was done as a means to provide more personalized support to students working on realistic design problems early in their training, leverage the benefits of peer learning strategies, and provide professional and leadership development opportunities to the TAs ahead of graduation. At the end of the course in which this was implemented, surveys were sent to students asking them to comment on their experience with this mentorship model, and the TAs of the course were interviewed to better understand theirs. This paper presents the results of these surveys and interviews, highlights the benefits and challenges of this approach, and provides recommendations for future implementations of this student support model

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 score0.123
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 integrity0.0000.000
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 head0.018
GPT teacher head0.287
Teacher spread0.269 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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