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Record W3217750024 · doi:10.3390/educsci11120765

Structural Timber Design in Curricula of Canadian Universities: Current Status and Future Needs

2021· article· en· W3217750024 on OpenAlexafffundabout
Hossein Daneshvar, Tahiat Goni, Sigong Zhang, Reed Kelterborn, Ying Hei Chui

Bibliographic record

VenueEducation Sciences · 2021
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsCanadian Wood CouncilUniversity of Alberta
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaUniversity of WaterlooUniversity of AlbertaUniversity of ManitobaUniversity of VictoriaUniversité du Québec à ChicoutimiLakehead UniversityUniversité du Québec à RimouskiUniversity of WindsorUniversity of CalgaryMcGill UniversityUniversity of TorontoUniversité de SherbrookeConcordia UniversityMcMaster UniversityUniversity of Northern British ColumbiaBritish Columbia Institute of TechnologyUniversité Laval
KeywordsCurriculumAccreditationEngineeringSustainabilityCivil engineeringArchitectural engineeringEngineering managementMedical educationPolitical science

Abstract

fetched live from OpenAlex

Due to the efficiency, sustainability, and advances in firefighting technologies, the allowable height for wood buildings was increased from 4 to 6 storeys in 2015 and will be further increased to 12 storeys in the 2020 edition of the National Building Code of Canada, as a result of the advent and application of mass timber products. To match the development in the industry and the increasing need in the market for highly skilled timber engineers, structural timber design curricula at the university level must evolve to train the next generation of practitioners. At most Canadian universities, structural timber design courses are mainly provided in civil engineering departments. In this study, 31 accredited civil engineering programs in Canada were reviewed for structural wood design content at undergraduate and graduate levels based on two surveys conducted in 2018 and 2020. In the 2018 survey, the percentage of structural timber design content was estimated and compared with other engineering materials (e.g., steel, concrete, and masonry), and a similar survey was repeated in 2020 to determine if any significant changes had occurred. In early 2021, two complementary questionnaires were sent to the instructors of timber-related courses across the country to collect quantitative information, including enrollment statistics, percentage dedicated to timber design in combined material courses, and potential topics deemed critical to support the design of modern timber structures. Based on the responses provided, and also on the availability of resources and the research ongoing, the content for five advanced-level courses is proposed to address the needs of the timber design community. The findings presented in this paper will assist the timber industry, government agencies, and educational institutions in effecting potential changes to university curricula to educate the next generation of timber design professionals who will possess the necessary skills and knowledge to meet the challenges in designing modern mass timber structures.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.251
Teacher spread0.226 · 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
Published2021
Admission routes3
Has abstractyes

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