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Record W4416366197 · doi:10.22329/jtl.v19i5.8855

Exploring the Prospective Biology Teachers’ Field-Trip Experiences as an Outdoor Learning Activity

2025· article· en· W4416366197 on OpenAlexvenueno aff
Gülcan Çetin

Bibliographic record

VenueJournal of Teaching and Learning · 2025
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsnot available
Fundersnot available
KeywordsOutdoor educationNatural (archaeology)Field (mathematics)Natural historyQualitative researchOutdoor activityContent analysisInformal learning

Abstract

fetched live from OpenAlex

The study aimed to identify the views of prospective biology students on the field-trip experience as an outdoor learning activity in both educational and social contexts. It employed a qualitative phenomenological analysis method. Participants included 38 prospective biology teachers in an education faculty in the Marmara region in Türkiye. The field trip was held at İzmir Bird Paradise, Natural History Museum and Botanical Garden in İzmir, Türkiye. Data was collected by an open-ended question form before and after the field trip. Content analysis techniques were used to analyze the data. The results of this examination showed that the students were mainly content with the social activities, courses, İzmir Bird Paradise, the Natural History Museum, and the Botanical Garden, respectively, after the field trip.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.003
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.045
GPT teacher head0.390
Teacher spread0.345 · 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 designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

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