The Development of Morphological Knowledge and Spelling in French
Bibliographic record
Abstract
The Frenchorthographic system is particularly difficult to learn because nearly 30% of words in the lexicon end with a silent letter. One metalinguistic skill that has been identified to facilitate spelling acquisition in French is morphological knowledge. This cross-sectional study investigated the construct of morphological knowledge, its development and its role in building accurate orthographic representations in a sample of francophone elementary students. We proposed that morphological knowledge, a superordinate process, encompasses children's implicit use of morphemes in everyday language and their conscious, targeted manipulation of morphemes. In the present study, we assessed children's recognition of morphogrammes, the silent-letter endings (SLEs) of root words that become pronounced in suffixed forms (e.g., the silent t in chant/ʃã/ [song] → chanteur /ʃãtœʀ/ [singer]). When spelling root words, children may mark morphogrammes by recalling morphologically related words in which the morphogramme is not silent - thus, morphological knowledge was hypothesized to positively predict morphogramme spelling. One hundred and twenty-three children in grades 1-3 were assessed on four measures of morphological knowledge, two measures of spelling recognition and a dictation of pseudowords to explore their inclusion of silent-letter endings in novel words. As expected, morphological tasks that required explicit morphological manipulations were harder than implicit ones. Moreover, first graders struggled to complete explicit morphological tasks, while third graders were near ceiling performance on implicit tasks. Nevertheless, the four tasks converged on a single morphological knowledge construct as confirmed by a factor analysis. Importantly, morphological knowledge explained unique variance in children's accurate representation of silent-letter endings after controlling for grade, reading for pleasure and general orthographic recognition of words. Finally, children rarely used silent-letter endings when spelling pseudowords; however, when they did, they displayed sensitivity to the appropriate phonological context for the letter used. The findings are in accord with theoretical models suggesting that the representations of letters without phonological value are difficult to construct and may remain fuzzy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".