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Record W4395452848 · doi:10.1080/03043797.2024.2346344

A scoping literature review of sociotechnical thinking in engineering education

2024· article· en· W4395452848 on OpenAlexafffund
Renato Rodrigues, Jillian Seniuk Cicek

Bibliographic record

VenueEuropean Journal of Engineering Education · 2024
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSociotechnical systemEngineering educationVariety (cybernetics)Engineering ethicsIdentity (music)EngineeringComputer scienceKnowledge managementEngineering managementArtificial intelligence

Abstract

fetched live from OpenAlex

Sociotechnical thinking (STT) has recently emerged in response to technical-social dualism. It is defined as the ability to identify, address, and respond to both social and technical dimensions of engineering. As the number of publications on STT increases, so does the need to map the literature. This paper provides a scoping literature review of STT in engineering education, focusing on research purposes, methodologies, findings, and potential gaps. Our examination of 25 papers indicates that research on STT in engineering education covers a variety of purposes and methodologies. Key findings in the literature provide a better understanding of students’ demonstration of and barriers to developing STT, the intersections between STT, engineering identity and culture, characteristics of STT, challenges and opportunities for teaching STT, and how prior knowledge and emotional connections can facilitate students’ development of STT.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.039
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.064
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0390.036
Science and technology studies0.0030.002
Scholarly communication0.0060.007
Open science0.0020.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.005
GPT teacher head0.242
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations12
Published2024
Admission routes2
Has abstractyes

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