MétaCan
Menu
Back to cohort
Record W2583800036

The Role of Environmental Education in the Ontario Elementary Math Curriculum

2016· article· en· W2583800036 on OpenAlexaboutno aff
Matthew Litner

Bibliographic record

VenueTSpace (University of Toronto) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationMath educationCurriculumEnvironmental educationPrimary educationPedagogyElementary mathematicsMathematicsSociology
DOInot available

Abstract

fetched live from OpenAlex

In 2007, the Ontario Ministry of Education (OME) mandated environmental education (EE) be integrated into all subject areas. However, in the Ontario math curriculum, there is not a single specific expectation that makes reference to EE. An initial literature review revealed there is a significant research gap when connecting math and the environment at the elementary level. Very few techniques, strategies and specific activities are proposed to help teachers integrate EE within the math curriculum. The primary research question that guides the study is: What role does environmental education play in the Ontario math curriculum at the elementary level? A qualitative case study approach is used as data is collected through individual, semi-structured interviews. Codes are created to identify two overarching themes. There are many challenges that restrict teachers from easily integrating EE and math. However, opportunities do exist for schools to overcome these challenges and successfully integrate EE and math. The OME must take a more active role in providing practical solutions that link EE and math. Teachers must be reflective and motivated to make their own connections between EE and math. Finally, administrators must encourage widespread integration of EE within all subjects, including math.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0040.000

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 head0.004
GPT teacher head0.218
Teacher spread0.214 · 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.

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueTSpace (University of Toronto)Same topicIndigenous and Place-Based EducationFrench-language works237,207