Differential Effects of Context and Feedback on Orthographic Learning: How Good Is Good Enough?
Bibliographic record
Abstract
In this study, students in Grade 2 read different sets of words under 4 experimental training conditions (context/feedback, isolation/feedback, context/no-feedback, isolation/no-feedback). Training took place over 10 trials, followed by a spelling test and a delayed reading posttest. Reading in context boosted reading accuracy initially; in contrast, the external support garnered from feedback resulted in heightened reading accuracy throughout training, as well as 1 week later. Different patterns were noted in spelling transfer; first, there was no effect of reading feedback on spelling at posttest. Second, the highest spelling scores were observed when children practiced reading words in isolation versus in context. In sum, providing feedback and/or context helps children read words accurately, which in turn seems to create orthographic representations that are “good enough” to support reading accuracy. However, reading in isolation seems to produce orthographic representations that are higher in quality, and therefore better able to support precise spelling.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".