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Record W1853943385 · doi:10.24908/pceea.v0i0.5846

DEVELOPING SYSTEMS THINKING SKILLS: A HIGH-SCHOOL COURSE ON ENGINEERING DESIGN

2015· article· en· W1853943385 on OpenAlexvenueno aff
Aharon Gero, Ofer Danino

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsnot available
FundersTechnion-Israel Institute of Technology
KeywordsTeamworkLikert scaleCourse (navigation)Critical thinkingMedical educationMathematics educationPsychologyEngineeringMedicineManagement

Abstract

fetched live from OpenAlex

A unique course has recently been developed at the Technion – Israel Institute of Technology for 12th grade students majoring in physics and electronics. During the course students are required to complete – on a team basis – various engineering tasks. The aims of the course are to increase its graduates’ motivation to study science and engineering, to develop their systems thinking skills, and to train them in teamwork. The study described in the paper examined to what degree the course’s second goal (developing systems thinking) had been attained. Thirty-two 12th graders participated in the study, which utilized quantitative tools alongside qualitative ones. The students were asked to fill out an anonymous questionnaire at the beginning and the end of the course. The questionnaire was a five-level Likert scale based on the CEST (Capacity for Engineering Systems Thinking) questionnaire. Additionally, semi-structured interviews were held with students at the end of the course. The study indicates an improvement in students’ systems thinking skills – characterized by a large effect size.

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)0.005
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.063
GPT teacher head0.309
Teacher spread0.246 · 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 designNot applicable
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

Citations4
Published2015
Admission routes1
Has abstractyes

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