The early assessment conundrum: Lessons from the past, implications for the future
Bibliographic record
Abstract
Abstract The early childhood educational field has garnered attention with initiatives to foster skill acquisition in young children prior to kindergarten entry. These initiatives, in conjunction with the rigorous demands of curricular reform and a burgeoning accountability movement, invoke questions regarding the adequacy of the instruments used to assess young children and the inherent difficulties in conducting such assessments. Because the effectiveness of education relies critically on the sound diagnoses of children's readiness for learning and the measurement of their subsequent progression throughout the schooling process, critical issues in early assessment must be addressed. An examination of past practices was synthesized with recent research to focus awareness on the insufficient content domain, restrictive context, adverse timing and questionable psychometric properties, specifically the inappropriate norms and low predictive validity, of many instruments. Both the implications of and compensatory strategies for each issue are considered. © 2004 Wiley Periodicals, Inc. Psychol Schs 41: 737–749, 2004.
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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 | 0.111 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.010 | 0.022 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.013 | 0.022 |
| 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".