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Record W4249568810 · doi:10.24908/pceea.vi0.14942

CURRICULUM RENEWAL FOR BETTER DESIGN-RELATED STUDENT OUTCOMES IN SECOND-YEAR CHEMICAL AND BIOLOGICAL ENGINEERING

2021· article· en· W4249568810 on OpenAlexaffvenue
Gabriel Potvin, Jonathan Verrett

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2021
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCurriculumDeliverableCornerstoneEngineering design processProcess (computing)Engineering managementComputer scienceProcess designMathematics educationEngineeringWork in processEngineering ethicsSystems engineeringMechanical engineeringPedagogySociologyPsychologyOperations management

Abstract

fetched live from OpenAlex

The Department of Chemical and Biological Engineering at UBC is currently undergoing a majorcurriculum renewal with the aim of modernizing the two undergraduate programs it offers to better prepare students for increasingly diverse industries. Part of this initiative aims to introduce design earlier and integrate it throughout the programs. At the core of the new 2nd year curriculum are two new cornerstone courses: CHBE 220 and 221 – Fundamentals of Chemical and Biological Engineering I/II. CHBE 220 is taken in term 1 and replaces a previous classicallystructuredphysical chemistry course and an introductory seminar on process technology. It focuses on basicchemical process design and analysis, drawing from thermodynamics and kinetics as needed to support design topics. CHBE 221, offered in term 2, replaces a previous introductory cell biology course, and focuses on industrial microbiology and bioprocess design, drawing from cell and molecular biology and physical chemistry as needed to support design tasks. Both courses include substantial term-spanning design projects. This paper outlines the content and structure of bothcourses and their place in the updated curriculum. It describes the integrated design projects and other course deliverables. Recommendations for future iterations of the courses are also presented.

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)0.001
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 score0.069
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

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