The effects of ABRACADABRA on reading outcomes: An updated meta‐analysis and landscape review of applied field research
Bibliographic record
Abstract
Abstract ABRACADABRA (ABRA) is an evidence‐based suite of interactive multimedia that engages learners in the development of core reading skills. This meta‐analysis presents an update of the research evidence about the effectiveness of ABRA for elementary students. It reports 91 effect sizes in six reading‐related outcomes for a sample of 7,388 students. Regardless of context and measurement type, the studies yielded positive effects of ABRA, ranging in magnitude from g+ = 0.080 for Vocabulary Knowledge to g + = 0.378 for Phonemic Awareness and reaching statistical significance in four outcome categories. This meta‐analysis adds to our understanding of the effectiveness of ABRA‐based reading instruction by exploring factors of research design, ABRA design and implementation contexts, and various student characteristics and offers implications for instructional practice.
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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 | 0.026 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.022 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".