Orthographic Learning of Inconsistent Non-Words in Good and Poor Spellers: Linking Dictation and Eye-Tracking Measures
Bibliographic record
Abstract
The French writing system contains numerous phoneme-to-grapheme inconsistencies that vary in their properties and distribution across words. These inconsistencies represent a major challenge for children learning to spell, especially for poor spellers or children with dyslexia-dysorthographia. To our knowledge, no study has examined how inconsistencies shape orthographic learning using both eye-movement data and dictation performance, in children with good and poor spelling skills. In this eye-tracking study, twenty French-speaking children aged 9 to 12 (good spellers: n = 10; poor spellers: n = 10) learned the spelling of six bisyllabic non-words containing an inconsistent syllable across three learning cycles while we recorded their eye movements. One week later, children completed delayed dictation and recognition tasks assessing long-term consolidation and retrieval. Both groups improved their spelling accuracy and exhibited shorter and fewer fixations across learning cycles, reflecting progressive orthographic learning. However, poor spellers fixated more often and longer on the inconsistent syllable and demonstrated weaker long-term retention, suggesting a less holistic encoding and difficulties consolidating orthographic representations over time. Future research should examine whether these learning patterns generalize to real words, classroom contexts, and to children with dyslexia-dysorthographia across broader learning conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".