Production of noun suffixes by Turkish‐speaking children with developmental language disorder and their typically developing peers
Notice bibliographique
Résumé
BACKGROUND: Turkish has a rich system of noun suffixes, and although its complex suffixation system may seem daunting, it can actually present a learning opportunity for children. Despite its unique features, Turkish has not been studied extensively, especially in the case of children with language deficits, such as developmental language disorder (DLD). Most of the extant studies are focused on bilingual children, and the results are somewhat mixed. AIMS: To focus on the noun morphology system of Turkish-speaking preschoolers with DLD and compare their use with that of two groups of typically developing (TD) children. Moreover, to investigate the nature of their noun suffix errors in detail. METHODS & PROCEDURES: We report data from a total of 80 monolingual children, 40 children with DLD (age range = 4;0-7;10), 20 TD age-matched children (4;0-7;3) and 20 younger mean length of utterance (MLU)-matched children (2;0-4;3). The data for this study came from language samples obtained from children in individual clinical assessment sessions. OUTCOMES & RESULTS: The children with DLD made less use of noun suffixes than both the younger and the age-matched TD children. The use of the unmarked (nominative case) form in place of an overt suffix was the most likely error by all groups. Suffix-change alternations required beyond vowel harmony seemed to pose real problems for these children. CONCLUSIONS & IMPLICATIONS: These results suggest that even when a language appears to provide significant advantages for the learning of noun morphology, children with DLD do not succeed in closing the gap. Certain factors such as morphophonological changes beyond vowel harmony, multiple allomorphs for the same suffix type and accusative suffixes that are not uniformly applied in the adult input were found to be significant predictors of the DLD group's difficulty with noun suffixes. Because these same factors can serve as characteristics of other languages, a child's difficulties might seem to be language specific (e.g., a particular allomorph in the language), but may actually be based on a broader difficulty (e.g., dealing with multiple allomorphs for the same suffix). Accordingly, factors that transcend a single language should be considered during clinical assessment and therapy. What this paper adds? What is already known on this subject? The current literature on the use of noun suffixes by Turkish-speaking children with DLD is very limited. Although Turkish is often described as a learner-friendly language, the degree to which children with DLD enjoy these learning benefits is unknown. What does this paper add to existing knowledge? Turkish children with DLD are less accurate in noun suffixes than both age-matched and younger control groups. For this group, the central problem seems to be increased complexity in morphophonology rather than difficulty with suffixation more generally. What are some of the clinical applications of this study? For clinicians who work with Turkish-speaking children with DLD, priority should be given to morphophonology. These children would benefit from treatment that focuses on how to attach different allomorphs to different open-class words. Because factors such as morphophonological complexity operate in other languages, the findings have broader clinical implications. In particular, regardless of the target language, clinicians should consider the possibility that these broader factors, rather than language-specific details, are the basis for a child's difficulty.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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