Efficient language processing necessitates some level of systematic mapping between word forms and meanings (Kirby et al., 2008; Dautriche et al., 2017). When words look similar but have unrelated meanings (e.g., ‘leopard’ vs. ‘leotard’), this inconsistent form-meaning mapping could interfere with word recognition (Forster & Hector, 2002; Bowers et al., 2005). For example, the activation of ‘leopard’ when seeing ‘leotard’ interferes with judging whether ‘leotard’ is an animal (Rodd, 2004). Little is known about whether similar interference occurs at the early stages of word learning.
In this study, I propose the form-meaning consistency (FMC) model, which offers a fine-grained analysis of the semantic relationships between words with similar forms. For example, ‘leopard-leotard’ exhibits low FMC due to similar forms but unrelated meanings, whereas ‘snort-snore’ shows high FMC with closely related forms and meanings.
This study examined the effect of form-meaning consistency on word learning (e.g., Does prior knowledge of ‘leopard’ interfere with learning ‘leotard’?). I designed and conducted a novel experiment where 50 adult native English speakers read short passages to learn 12 pseudowords that differ in their form-meaning consistency with known words. For example, I investigated whether the activation of ‘bucket’ interfered with learning the meaning of ‘burket,’ a fictional animal, in the early stages of acquisition. Learning was measured by semantic relatedness rating tasks.
The findings indicate that lower FMC interfered with the semantic learning of novel words. Specifically, the activation of semantically less related orthographic neighbors led to longer response time and biased ratings in semantic tasks. This interference effect was most salient in delayed semantic tasks and was mitigated in immediate tasks. The analysis reveals various mechanisms through which FMC influences the retrieval of word meaning and decision on semantic relatedness.
This study contributes to the understanding of how the brain's semantic network processes and integrates novel linguistic information, highlighting the significance of form-meaning mappings in efficient language learning and usage. By extending the current understanding of the role of form-meaning mapping in word recognition to the realm of word learning, this research provides insights into the mechanisms and cognitive processes underlying vocabulary learning from reading. It also has significant implications on more effective language teaching strategies, particularly in designing learning materials that minimize interference and optimize learning.