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Record W1973292488 · doi:10.1109/mse.2013.6566701

Integrating creativity into elementary electrical engineering education using CDIO and project-based learning

2013· article· en· W1973292488 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCDIOEngineering educationCreativityEngineeringMechatronicsMathematics educationAppealEngineering ethicsComputer scienceEngineering managementPsychologyElectrical engineeringPolitical science

Abstract

fetched live from OpenAlex

Microelectronics and embedded systems industries are seeking creative engineers to create new and innovative technologies at the same time as a decline in post-secondary engineering enrollment. Studies show that students may lose interest in science, mathematics, engineering and technology (STEM) as early as elementary school, believing that these areas are not innovative or creative. Using the CDIO Initiative framework for engineering education, this study looks at the development of a creative, project-based learning program called Exploring Electrical Engineering, designed to teach an introduction to electronics and electricity through integration with other disciplines, such as English, social studies, physical education and fine arts. By introducing a creative and cross-disciplinary component to STEM education, we propose to increase the appeal of electrical engineering to children who have expressed interest in other subjects, and encourage innovative, exploratory problem-solving.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.588

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 head0.007
GPT teacher head0.230
Teacher spread0.223 · 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

Citations20
Published2013
Admission routes1
Has abstractyes

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