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Record W4236216447 · doi:10.32920/14638575

A practical servomotor project: combining the Web with simulation tools to solidify concepts in undergraduate control education

2021· preprint· en· W4236216447 on OpenAlexafffundabout
M S Zywno, D C Kennedy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsToronto Metropolitan University
FundersRyerson University
KeywordsComprehensionEnthusiasmComputer scienceCurriculumProcess (computing)Control (management)Course (navigation)MultimediaSoftware engineeringHuman–computer interactionEngineeringArtificial intelligencePedagogyProgramming languagePsychology

Abstract

fetched live from OpenAlex

Current technology enables the lecturer to use computer tools to enhance the conceptualisation of lecture material. This can be especially useful in an engineering curriculum, as the course material can be rendered less abstract through visual illustration of difficult mathematical concepts. In this paper, we present an example of a multimedia enhanced course in linear control theory, taught by authors at Ryerson Polytechnic University (Toronto, Canada). In our implementation of the course, we combine software simulations of practical systems to illustrate control theory concepts with extensive online course notes to assist with comprehension. Followup analysis shows that the use of the WWW and computer tools to enhance the learning process leads to increased enthusiasm, comprehension, and information retention. A review of the process required to create the technology enabled learning environment shows that initially there is a great deal of work involved. However, we conclude that the effort is justified by allowing a positive qualitative change in the way we educate engineering students.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.337
Teacher spread0.311 · 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
Published2021
Admission routes3
Has abstractyes

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