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Record W4308911747 · doi:10.24908/pceea.vi.15830

RealEngineering: Space – Designing the Community-Applied Space Engineering Program

2022· article· en· W4308911747 on OpenAlexafffundvenueabout
Olivia Alsop, Raghad El-Shebiny, Franz Newland

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2022
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsYork University
FundersYork University
KeywordsSpace (punctuation)Work (physics)Engineering educationSustainabilityCubeSatIndigenousEngineeringEngineering ethicsEngineering managementComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Engineering education is still largely offered through traditional, content-heavy approaches, with key technical topics in individual courses separate from those that emphasize the practice of the engineering profession, resulting in fragmented student workloads. Traditional assessments do not accommodate students’ unique, diverse learning perspectives. These issues fail to recognize that engineering is above all else a community-of-practice, requiring practitioners to demonstrate innovation and resilience to address today’s complex challenges in sustainable ways.
 More recent programs adopt project-based pedagogies, that engage learners in engineering problems that affect their communities. This paper proposes taking the project focus further, with a structure that allows faculty and students to collaborate on real-world engineering work that is not just done for, but also with, the community, and with sustainability built in. Such an approach establishes an overarching connection between the “work” of an engineer and what it is to be a future engineer for society.
 The authors are developing a 4-year space engineering program proposal, where students from all years will collaborate to design, build, launch and operate a cubesat for, and with, the community as the full focus of their 4-year degree. A six-week pilot slice of the program took place in the summer of 2021 with 20 students from all undergraduate year groups collaborating on a community-focussed, sustainable small space-mission design activity to change power dynamics around water quality data in northern and indigenous Canadian communities. Students worked in organizational teams, with structured teambuilding and collaboration time, focussed working sessions from subject-matter-experts, microcredential learning and unstructured team time to advance their project. This culminated in a mission concept review with a team of expert, industry and community partners.
 This paper presents some of the key ideas that informed the program, and the tools used to frame the learning journey in an undergraduate engineering degree. The pilot demonstrated students’ readiness to take on complex, unstructured challenges and organize themselves, and the potential to offer undergraduate learning spaces that have a very different connection to community and global issues.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
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
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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

Citations0
Published2022
Admission routes4
Has abstractyes

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