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Record W420696810 · doi:10.5206/cie-eci.v40i1.9170

The Schema-based Mathematics Study: Enriching Mathematics Teaching and Learning Using a Culture-sensitive Curriculum

2011· article· en· W420696810 on OpenAlexafffundvenueabout
Anthony N. Ezeife

Bibliographic record

VenueComparative and International Education · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsUniversity of Windsor
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Windsor
KeywordsCurriculumIndigenousMathematics educationSchema (genetic algorithms)PedagogyIndigenous cultureSociologyMathematicsComputer scienceBiology

Abstract

fetched live from OpenAlex

Declining enrolment in mathematics and related fields is a common problem in present-day academic world. In many indigenous cultures worldwide, the flight from mathematics and science, noticeable even in advanced, technologically oriented societies, assumes alarming proportions. In Canada, for example, low enrolment and high dropout rates from mathematics and science courses are common among aboriginal students. The few who persist and complete their mathematics courses in high school often end up with low grades, a situation that has resulted in the paucity of qualified aboriginal students in mathematics-related careers at higher levels of education. Several researchers have opined that the situation arises due to the lack of relevance of school mathematics and science to the aboriginal learner's everyday life and culture. Therefore, they argued that cultural practices, ideas, and beliefs (the students‘ schema) that would connect the school to the community in which it exists and functions should be incorporated into the mathematics curriculum. This study implemented an innovative (culture-sensitive) mathematics curriculum, developed with the active participation of community Elders, in the Walpole Island First Nation elementary school in Ontario, Canada. Results showed that students who were taught with the culture-sensitive curriculum performed significantly better than their counterparts taught with the existing (regular) provincial curriculum. Les inscriptions décroissantes en mathématiques et domaines annexes représentent un problème majeur de niveau international dans le monde académique. Cette fuite des mathématiques et des sciences qui a lieu non seulement dans les cultures autochtones mais aussi dans les sociétés technologiquement avancées prend des proportions alarmantes. Au Canada par exemple, les étudiants autochtones s‘inscrivent peu en mathématiques et en sciences ou abandonnent souvent ces études. Ceux qui persistent et qui finissent leurs cours de mathématiques au lycée obtiennent souvent des notes assez basses, une situation qui entraine une pénurie d‘étudiants autochtones qualifiés en mathématiques et domaines annexes à l‘université. Certains chercheurs pensent que cette situation est due au fait que les mathématiques et sciences scolaires n‘ont aucun rapport avec la vie quotidienne et la culture des étudiants autochtones. C‘est la raison pour laquelle ils pensent que les pratiques culturelles, les idées et les croyances des communautés locales (schémas des étudiants) devraient être insérées dans les programmes de mathématiques. Ceci permettrait de connecter l‘école directement aux communautés. Cette étude a mis en œuvre un curriculum de mathématiques innovant et sensible à la culture. Il a été conçu avec la participation active des anciens de la communauté dans l‘école élémentaire des Premières Nations de l‘Île de Walpole en Ontario au Canada. Les résultats montrent que ceux qui ont suivis les cours par le biais du curriculum basé sur la culture ont eu des résultats nettement supérieurs à ceux qui ont suivi les programmes provinciaux officiels.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.216
GPT teacher head0.469
Teacher spread0.253 · 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

Citations5
Published2011
Admission routes4
Has abstractyes

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