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Record W4312105823 · doi:10.5430/wje.v12n6p49

The Effect of E-STEM Education on Students’ Perceptions and Engineering Design Process about Environmental Issues

2022· article· en· W4312105823 on OpenAlex
Asli Koculu, Şefika Girgin

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Journal of Education · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFocus groupEnvironmental educationEngineering educationProcess (computing)Mathematics educationContent analysisPerceptionScience educationEngineering design processPsychologyEngineeringPedagogySociologyEngineering managementComputer scienceSocial scienceMechanical engineering

Abstract

fetched live from OpenAlex

E-STEM (Environmental, Science, Technology, Engineering and Mathematics) refers to the integration environmental education into STEM education and can have important role on students’ understandings and engineering design process about environmental issues such as plant growth, acid rains, pollution, sustainable agriculture etc. since it engages students in real-world environmental problem-solving that integrates science, technology, engineering, and math. In this manner, the aim of this study was to investigate the effect of E-STEM Education on fifth grade students’ perceptions and their engineering design process about environmental issues. To reach this aim, a one-group pre- and post-test model was used. The research group of study is five 5th grade students at private school, Istanbul, Turkey. The data was collected with open-ended questions, focus group interview and researchers’ observation notes. In data analysis, students’ responses to open-ended questions were analyzed with content analysis and classified in terms of adequacy. Transcribed discussions from focus group interview and researchers’ observation notes were assessed based on Engineering Design Process Framework. As a result of the study, students’ perceptions and engineering design process about environmental issues improved through E-STEM Education.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.274
Teacher spread0.260 · 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