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Record W3192402858 · doi:10.18260/1-2--37659

Remote Delivery of an Introductory Architectural Engineering Design-Build Activity

2024· article· en· W3192402858 on OpenAlex
Spencer A. Arbuckle, Patrick Angkiriwang, Joyceline Nathaniel, Rania Al-Hammoud, Scott Walbridge

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2021 ASEE Virtual Annual Conference Content Access Proceedings · 2024
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceArchitectural designSoftware engineeringArchitectural engineeringSystems engineeringEngineeringArchitectureVisual arts

Abstract

fetched live from OpenAlex

Abstract The first Architectural Engineering (AE) class at the University of X (UX) began in fall of 2018. The mandatory co-op work experience, studio component each semester, and collaboration with the UW School of Architecture are features of the program that make it unique in North America, just to name a few. In order to provide an introduction at the beginning of the school year that would adequately capture the essence of the program, a tried-and-true hands-on engineering project model at UX called 'Design Days' was adapted for the AE program. In 2018, the inaugural two-day design-build project called 'AE Design Days' was held wherein first year students worked in groups to design a piece, or set, of furniture that enhanced an assigned site in a UX Engineering building. The objectives of the project were to provide an 'ice-breaking' opportunity between students, as well as with the faculty; introduce the students to the AE course content, especially as it relates to the design process; provide opportunities for the students to work with their hands building models; and, to allow for the course instructors to gauge the skillset and prior knowledge of the incoming students[1]. Following the success of the first AE Design Days event, the same project model was implemented 2019, with minor modifications to improve the event logistics and student experience. Following the transition to online learning as a result of the COVID-19 pandemic, a dramatic overhaul of the event was required to hold the most recent iteration in the fall 2020 semester. The intention was to have the same objectives for the project; however, with the students learning entirely remotely, and most doing so from home, some objectives were emphasized (e.g. student interaction). The event objectives were set to prime the students for the project-oriented courses in the AE program, through aspects inductive and experiential learning, and combined with an effort to address the specific challenges of online learning. The online format of the event lent several constraints, as it would not be possible to build models to the extent that it had been done in previous years. This paper discusses the planning process and implementation of the virtual AE Design Days event, as well as the perceived challenges of online learning within Architectural Engineering, but also the successes of the event from both the student and instructor perspective.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score1.000

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 communication0.0000.002
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 head0.031
GPT teacher head0.256
Teacher spread0.224 · 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