MétaCan
Menu
Back to cohort
Record W3027933870 · doi:10.1080/14729679.2020.1769694

Meaning-making of student experiences during outdoor exploration time

2020· article· en· W3027933870 on OpenAlexaffabout
Stephen Berg, Brent Bradford, Joe Barrett, Daniel B. Robinson, Fabiano Marques Camara, Tess Perry

Bibliographic record

VenueJournal of Adventure Education & Outdoor Learning · 2020
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsSt. Francis Xavier UniversityBrock UniversityConcordia University of EdmontonUniversity of British Columbia
Fundersnot available
KeywordsOutdoor educationPsychologyMeaning (existential)PedagogyFocus groupNatural (archaeology)Sense of placeThematic analysisMathematics educationSocial psychologySociologyQualitative researchGeographySocial science

Abstract

fetched live from OpenAlex

The purpose of this study was to gather the thoughts and opinions of students and their teachers around the benefits of outdoor exploration time. Students within three grade 3 classes in one western Canadian province were afforded opportunities to connect with the outdoor elements and each other in designated forested areas near their school, while also enjoying free outdoor learning time. Semi-structured focus group interviews were conducted for participants to share their experiences. Using a thematic approach, four key findings emerged from these interviews: expanding perspectives, connection to nature, sense of choice, and enjoyment. According to the findings, affording an outdoor space and the opportunity for students to spend time outside on a consistent basis may be an important way to give students the chance to learn in an organic way from nature, form deep connections to nature, develop within themselves a sense of choice, and find enjoyment in the natural environment.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.011
Scholarly communication0.0070.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.355
Teacher spread0.330 · 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

Citations13
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Adventure Education & Outdoor LearningSame topicOutdoor and Experiential EducationFrench-language works237,207