The Use of Authentic Assessment to Report Accountability Data on Young Children’s Language, Literacy and Pre-math Competency
Bibliographic record
Abstract
This validity study examined the validity of Assessment, Evaluation, and Programming System, 2nd Edition (AEPS®), a curriculum-based, authentic assessment for infants and young children. The primary purposes were to: a) examine whether the AEPS® is a concurrently valid tool for measuring young children's language, literacy and pre-math skills for accountability purpose and b) explore teachers' perceptions on using authentic assessment and standardized tests. This was accomplished through implementing both quantitative and qualitative methods. Findings from the study indicated (a) the AEPS® is a concurrently valid (b) there were both advantages and disadvantages of using authentic assessment such as the AEPS® and using standardized tests based on teachers' perceptions, however, the practical issues of using the authentic measure can be addressed by providing in-depth trainings to teachers and increasing teachers' familiarity with their children; and (c) families preferred authentic assessment such as the AEPS® because it is easier.
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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 | 0.049 | 0.179 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".