Three approaches to financial numeracy education in secondary mathematics textbooks
Bibliographic record
Abstract
This article examines the integration of financial numeracy in secondary mathematics textbooks. It addresses the gap in literature on how financial concepts are portrayed in textbooks, contributing to the establishment of financial numeracy as a field of research and practice. The study analyzed financial numeracy tasks in three published textbook collections from the Canadian Province of Quebec, using qualitative data software to code tasks by collection, grade, mathematical domain, and financial numeracy approach. The results revealed a higher frequency of financial tasks in early secondary grades compared to late (streamed) grades, with a shift in focus from contextual to conceptual approaches in later grades. Algebra and arithmetic domains contained most financial tasks, with significant differences among textbook collections. The findings suggest a need for textbooks to balance mathematical and financial aspects in tasks, and for teachers to receive support in content and pedagogy related to financial numeracy. The study advocates for a nuanced understanding of financial concepts in mathematics, approaching financial numeracy as sensemaking in financial situations (which goes solving problems with defined variables for decision making).
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".