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Record W2747902725 · doi:10.18260/1-2--10600

Simulation And Animation Of Mechanical Systems To Enhance Student Learning

2020· article· en· W2747902725 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceAnimationVariety (cybernetics)Process (computing)Domain (mathematical analysis)Human–computer interactionFocus (optics)VisualizationSoftware engineeringMultimediaArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

There are many applications in mechanical engineering whose analysis or design procedures not only require tedious computations but also are prone to error so that neither instructors nor students are keen to focus on the details of the subjects. They are not enthusiastic to pursue the lengthy process of the old fashioned designs although widely used in the industry. Thus, they incline to use commercial programs which are more similar to a black box. The use of educational computer programs, on the other hand, could effectively alleviate the problems because students may understand the subject and effects of many parameters involved without wasting their time for repetitive computations. It can also help them to examine the results and track the errors and see where the problems lie.  Educational computer programs are different from commercial ones in many aspects. The educational programs must have a sufficiently generic framework to deal with a large variety of possible options that may or may not be used in real applications. More precisely, commercial software often works in a limited domain whose extremes are well defined for both users and programmers, whereas educational tools should be able to satisfy curious students who naturally prefer to test the programs with irregular examples. Besides, the educational computer program must have an interesting graphical user interface including visualization and animation to motivate the users, and provide ample information and background about the application, pertinent parameters, possible errors, etc. Thus, the development of a useful educational program would be challenging for it requires a deep understanding of the subject, programming, and educational skills. The Department of Mechanical and Industrial Engineering at the University of Toronto has been interested in the development of a series of software programs that can be used by instructors, teaching assistants, and students involved in the undergraduate curricula. The programs are primarily developed for the teaching purposes, but they can be used in distance learning, student projects, research laboratories, and educational workshops. This paper presents two sample programs developed for two mechanical systems including mechanical vibration systems and cam and follower systems. Feedback from students who have worked with these programs has been so positive that it encourages us to consider more such applications and develop the programs, accordingly.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.270

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 head0.011
GPT teacher head0.280
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

Quick stats

Citations2
Published2020
Admission routes2
Has abstractyes

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Same topicExperimental Learning in EngineeringFrench-language works237,207