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Record W4390484131 · doi:10.25071/1916-4467.40694

Students’ Perspectives of Transdisciplinary Financial Literacy Education in Ontario

2023· article· en· W4390484131 on OpenAlexaffvenueabout
Murdoch Neil Matheson, Christopher DeLuca, Ian Matheson

Bibliographic record

VenueJournal of the Canadian Association for Curriculum Studies · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsFinancial literacyCurriculumLiteracyPedagogyMedical educationPsychologySociologyMathematics educationFinanceBusinessMedicine

Abstract

fetched live from OpenAlex

In increasingly uncertain economic times, education curricula around the world are changing to include the topic of financial literacy for students. This article reports the findings of a financial literacy study that examined the perspectives of students on their experiences with transdisciplinary teaching and learning of personal financial literacy. In this study, 344 post-secondary students reflected on their educational experiences in Ontario secondary schools by completing a quantitative survey composed of questions and self-assessments related to personal financial literacy curricula. While students felt that personal financial literacy education was important, they felt that there was a need for more knowledge and understanding in secondary school. Further, survey data identified variations in the personal financial literacy education students received that was linked to the stream (advanced or general) students were enrolled in. The findings are discussed, with particular attention to how students’ perspectives can inform policy and curriculum design moving forward.

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)0.004
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 score0.173
Threshold uncertainty score0.348

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0240.006
Scholarly communication0.0050.001
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.290
Teacher spread0.275 · 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
Published2023
Admission routes3
Has abstractyes

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Same venueJournal of the Canadian Association for Curriculum StudiesSame topicFinancial Literacy, Pension, Retirement AnalysisFrench-language works237,207