What do Students Learn in the Numbers for Life Course at McMaster University? Assessing students’ improvement and retention of numeracy knowledge and skills
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
Our society is surrounded by numbers and throughout our lifetime we all experience numeric situations daily. Developing necessary numeracy skills is a crucial part of being able to fully participate in modern technological society and engage in the world around us. The course Numbers for Life at McMaster University (Math 2UU3) is designed to teach about critical numeracy problems that we are faced with in our daily lives and is offered to non-mathematics major students in their second year or above. Students in the course were surveyed three times through a pre-test, post-test and delayed post-test, that was written one year after course completion. Using the responses to these survey instruments, this thesis focuses on studying the retention of a student's ability to understand numeric information and their ability to communicate their answers. Having good retention is key for a learner to successfully apply what they have learned in future real-life scenarios. By studying the retention of students' responses to commonly encountered real-world math problems, we can determine how valuable courses like Numbers for Life are to have in place for all students.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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