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Record W3177188188 · doi:10.1177/03064190211025954

A build-at-home student laboratory experiment in mechanical vibrations

2021· article· en· W3177188188 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Mechanical Engineering Education · 2021
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSet (abstract data type)Coronavirus disease 2019 (COVID-19)Bifilar coilComputer scienceSimple (philosophy)MultimediaHuman–computer interactionEngineeringMathematics educationPsychologyMedicine

Abstract

fetched live from OpenAlex

The Covid-19 pandemic has caused many university educators to redesign their teaching to online delivery. This can be an effective approach for theoretical and conceptual teaching, but it is challenging to provide practical laboratory experiences. The objective here is to design a hands-on laboratory experience that can safely be undertaken by students remotely and that has substantial educational content. A new experiment was designed featuring a bifilar pendulum that students build themselves from readily available low-cost materials. This simple vibrating system has a surprisingly rich set of interesting physical characteristics that provide several important learning points. Initial trials indicate good student experience with the new experiment, notably an appreciation for the "do-it-yourself" aspect of the apparatus construction. The self-directed features and multiple learning features of the new student experiment make it attractive for use during Covid-19 times and beyond.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.275
Teacher spread0.269 · 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