Bibliographic record
Abstract
This study examined the predictive qualities of a competency-based mathematics assessment relating to a traditional mathematics assessment. The competency-based assessment is a school district developed assessment called the Student Numeracy Assessment & Practice (SNAP). The traditional mathematics assessment is the Foundation Skills Assessment (FSA), developed and provincially mandated by the British Columbia Ministry of Education. The study's methodology examines the correlations between student achievement on SNAP and the FSA. The study controls for social economic status (SES), ethnicity, special education designation, and gender in the context of middle school learning in Chilliwack, British Columbia and answers the question: Does student achievement on the grade 6 SNAP predict achievement on the grade 7 numeracy FSA? Additional research questions consider the impact of independent variables (reading achievement, report card mathematics achievement, and mathematical student self-efficacy) on both the FSA and SNAP assessments. This study's methodological approach involved the correlation of student cohort achievement data limited to the 2018/19 cohort of year six (grade 6) students in the Chilliwack School District. The study followed this cohort's achievement through completing the grade 7 FSA in the fall of 2019. There are 786 students represented in the sample size. The study showed a strong correlation r = .60 between SNAP and FSA. Additional findings included similar correlations between both assessments and classroom-based letter grades. Final findings included a strong correlation between FSA numeracy achievement and FSA reading achievement. Remarkably, this correlation was not evident between SNAP and FSA reading, indicating a striking difference between the two assessments. Identifying a competency-based numeracy assessment that does not have significant correlation to reading achievement is the most significant outcome of this 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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".