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Record W3005533686 · doi:10.1109/te.2020.2965817

BLDC Motor-Driven Fluid Pumping System Design: An Extrapolated Active Learning Case Study for Electrical Machines Classes

2020· article· en· W3005533686 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.

Bibliographic record

VenueIEEE Transactions on Education · 2020
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsMohawk College
Fundersnot available
KeywordsPraxisMathematics educationComputer scienceMultidisciplinary approachActive learning (machine learning)Knowledge managementPsychologyEngineeringEngineering ethicsEngineering managementSociologyPolitical scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Contribution: A project-based active learning approach with the collaborative pedagogical environment is used to train electrical engineers, focusing on loading characteristic of motors where extrapolated knowledge from advanced classes and feedback from the industry professionals are used to engage fellow students to improve their conceptual and applicatory learning. Background: Forces of globalization, including engineering education's multicontingent epistemological structure requiring a broad-based skill set, linking academia, and industry necessitate specific pedagogical intervention. The project-based pedagogy contextually embedded in collaborative environment has proven to serve as an ideal approach to address the scenario. Despite its demonstrated efficacy, its implementation has been sporadic, globally, and systemically within most educational institutions. In that light, this article is expected to stand as a strengthening paradigm simultaneously with conventional didactic orientation to fill that void. Intended Outcomes: Based on the academic needs and industrial demands, the specific techniques employed greater primacy on augmenting content mastery, critical thinking, and problem-solving skills that may have higher sustainability. Application Design: Project-based model that has been tested here is embedded in multidisciplinary and collaborative teaching package emphasizing problem probing and prescription. This approach underlies a very holistic orientation, providing a greater connection between theory and praxis, thereby having a higher appeal to theoreticians, learners, and the end-users. Findings: Extrapolated knowledge from graduate and upper-division undergraduate courses can be used to train lower-division undergraduate students. A positive trend in student learning outcome in power courses and a very positive feedback from industry professionals reflect the active learning model effectiveness accompanied by actual student test scores.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.537
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 integrity0.0000.000
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 head0.027
GPT teacher head0.284
Teacher spread0.257 · 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