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Record W2920543705 · doi:10.5430/wje.v9n1p188

Determining the Concept of Organic Agriculture Perceptions of Pre-service Classroom and Science Teachers Using Phenomenographic Method

2019· article· en· W2920543705 on OpenAlexvenueno aff
Tülay DİZİKISA, Pınar Ural Keleş

Bibliographic record

VenueWorld Journal of Education · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumPerceptionAgriculturePsychologyAgricultural educationMathematics educationService (business)Sample (material)Science educationData collectionMedical educationPedagogyGeographySociologyMedicineChemistrySocial scienceBusinessMarketing

Abstract

fetched live from OpenAlex

This study was carried out to determine the perceptions of pre-service classroom and science teachers related to theconcept of organic agriculture. The sample of the study consisted of 85 pre-service teachers, 57 from the Department ofClassroom Teaching and 28 from the Department of Science Teaching in Ağrı İbrahim Çeçen University, in theacademic year of 2016-2017. In the study, a semi-structured questionnaire which includes the statement “To me,organic agriculture means……” was used as data collection tool. In this study, the organic agriculture perceptions ofthe pre-service teachers were determined under five main categories. The ratio of 'natural agriculture, which has thehighest percentage among these categories, is 41% among the pre-service classroom teachers while this ratio is 65%among pre-service science teachers. It is among the recommendations of the study that the subjects related to organicagriculture are removed from the elective courses and placed in the science curriculum.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.142

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.028
GPT teacher head0.302
Teacher spread0.274 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2019
Admission routes1
Has abstractyes

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