Scaling Up and Moving In: Connecting social practices views to policies and programs in adult education
Bibliographic record
Abstract
The social practices framework has had a major impact on adult literacy and numeracy research over the past quarter century in the US, the UK and other countries. To date, the social practices view has had far less influence on the development of policies and programs in adult literacy and numeracy education. To help this happen, new kinds of assessment tools aligned with the social practices framework are needed to support appropriate changes in curriculum design, learner assessment and program evaluation.In this article research is presented that illustrates how measures of adults’ engagement in literacy and numeracy practices can be used in conjunction with well-entrenched proficiency measures to provide a richer quantitative framework for adult literacy and numeracy development. Longitudinal data about learners indicate that adult education programs are more closely aligned with practice engagement measures than with proficiency measures. Program participation leads to increased practice engagement that, over time, leads to the very gains in proficiency currently valued by policy makers.
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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 | 0.034 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.043 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".