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Record W4320898510 · doi:10.5703/1288284317601

Integrated STEM: Impact of Engineering Design and Computer Science in STEM Labs

2023· article· en· W4320898510 on OpenAlex
Jason Morphew, Rubén López, Amir Bralin, Ravishankar Chatta Subramaniam, N. Sanjay Rebello, Carina M. Rebello

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
TopicExperimental Learning in Engineering
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsScience and engineeringMathematics educationComputer sciencePerceptionDesign elements and principlesEngineering ethicsEngineeringSoftware engineeringPsychology

Abstract

fetched live from OpenAlex

By integrating physics laboratories with engineering design and computer science, students apply physics principles to ill-structured and complex problems, engage in knowledge transfer, and gain interest in STEM. The introductory physics labs at Purdue have been updated to include engineering design and computer science principles that ground physics in authentic problems. Integrated labs have been evaluated using student perception post-surveys, student course performance, interviews, and case-study observations. Preliminary results indicate that integrated physics labs promote transfer, enhanced metacognitive skills, student interest, and motivation.

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 score0.107
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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