Engineering Students’ Perception of Financial Mathematics-An empirical study based on the EAPH-MF scale
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.
Bibliographic record
Abstract
In this study, the EAPH-MF test was administered to a sample of undergraduates, with the purpose of comparing the results with those observed in the original research of “Author” (2011), regarding students’ perception and attitudes toward financial-mathematics courses. The sample comprised 209 Industrial-Engineering students, who were enrolled in the Mexican university “Instituto Tecnológico Superior de Tierra Blanca”, and had finished one or more financial-mathematics courses. The study replicated the same method applied in the original research, aiming to assess the relevance of the variables under study and their probable correlation. It was observed that, whenever the teaching-learning process incorporated the variables of the EAPH-MF scale as a didactic strategy, the results validated similar behaviors among students in both samples. These variables -the history of mathematics, spreadsheet programming, design of simulators, a computer platform, and the participation of virtual communities- accounted for 60% of the variance of the phenomenon under study.
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 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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 it