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Record W3177602129 · doi:10.24908/pceea.vi0.14886

INTEGRATING LEARNING OBJECTIVES IN A MULTI-SEMESTER SUSTAINABLE CONSERVATION DESIGN PROJECT FOR FIRST-YEAR STUDENTS DURING A PANDEMIC

2021· article· en· W3177602129 on OpenAlexafffundvenue
Libby Osgood, Nadja Bressan

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2021
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Prince Edward Island
FundersUniversity of Prince Edward Island
KeywordsProject-based learningEngineering managementEngineeringMathematics educationPsychology

Abstract

fetched live from OpenAlex

Project selection for first-year design courses can be complicated by the limited skill level of students in their first semester of an engineering program and the scalability required for multiple sections and large classes. Additionally, the project must address the course's learning objectives and provide a sense of authenticity to help students understand the role of engineers in society. Afirst-year design course can be seen by students as the ‘introduction to engineering,’ enabling them to decide whether to pursue engineering as a profession or not. In addition to the already taxing demands imposed on a project for a first-year design course, students at the University of Prince Edward Island completed a design project encompassing two engineering courses andcontributed to a scientific research study on bat conservation. Partnering with researchers in the Atlantic Veterinary College, students designed, built, and installed bat houses equipped with sensors to remotely collect temperature, humidity, and the presence of individual bats within the colony. Constructing 21 bat houses promoted conservation efforts of bats across the province and taught students the critical role of engineers in a sustainable society. This paper presents a discussion on project selection for first-year design courses, how the learning objectiveswere met for two first-year design courses during a pandemic, and describe the community partner's role\ throughout the design project.

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)0.002
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 score0.106
Threshold uncertainty score0.775

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.012
GPT teacher head0.238
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

Citations0
Published2021
Admission routes3
Has abstractyes

Explore more

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