MétaCan
Menu
Back to cohort
Record W2617147240 · doi:10.12973/eurasia.2017.00833a

Teaching and Learning Science Outdoors in Schools’ Immediate Surroundings at K-12 Levels: A Meta-Synthesis

2017· article· en· W2617147240 on OpenAlex
Jean‐Philippe Ayotte‐Beaudet, Patrice Potvin, Hugo G. Lapierre, Melissa Glackin

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEurasia Journal of Mathematics Science and Technology Education · 2017
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsScience learningOutdoor educationMathematics educationScience educationPsychologyEnvironmental educationLearning sciencesPerceptionExperiential learningPedagogy

Abstract

fetched live from OpenAlex

This literature review synthesizes empirical data of 18 articles published between 2000 and 2015 about teaching and learning science outdoors from kindergarten to secondary levels (K–12). We asked four questions: (1) What are the general characteristics of the corpus of studies on teaching and learning science outdoors in schools’ immediate surroundings at K–12 levels? (2) What are the authors’ aims for conducting studies about teaching and learning science outdoors? (3) What are the main outcomes related to teaching and learning science outdoors in schools’ immediate surroundings? (4) What further studies should, according to the selected articles, be conducted in the future? We identified three categories of authors’ aims: environmental education, science education, and outdoor education. The main outcomes are classified into four categories: 1) learning, 2) student attitude or interest, 3) other students’ perceptions, and 4) challenges to outdoor science teaching. Finally, in light of the review, we discuss how further studies should consider learning outcomes, students’ attitudes, challenges, and methodological guidelines.

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)0.007
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.053
GPT teacher head0.374
Teacher spread0.321 · 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