In the context of the learning, teaching, and assessment of second language (L2) speaking skills, L2 fluency has been regarded as one of the important constructs. In order to distinguish different conceptualizations of fluency, Segalowitz (2010) proposed three variants of fluency: utterance fluency (UF; i.e., observable temporal features of speech), cognitive fluency (CF; i.e., the speaker's ability to manipulate L2 knowledge efficiently), and perceived fluency (PF; i.e., listener's subjective judgements of fluency). Among these three subconstructs of "fluency", the relationship between PF and UF has been extensively examined (Bosker et al., 2013; Derwing et al., 2004; Suzuki & Kormos, 2020), it is still unclear how CF is associated with UF (De Jong et al., 2013; Kahng, 2020). To this end, the current study examined the contribution of CF to UF, using structural equation modelling (SEM).
A set of CF and UF measures were collected from Japanese-speaking learners of English (N = 128). Using a range of psycholinguistic tests, CF was assessed in terms of linguistic resources and processing speed at the different linguistic levels: vocabulary (vocabulary size, lexical retrieval speed), grammar (sentence construction speed, grammaticality judgement test) and pronunciation (articulatory speed). In order to measure UF, the speech data were elicited via four speaking tasks: argumentative task, picture narrative task, and reading-to-speaking, and reading-while-listening-to-speaking task. The speech data were analysed in terms of three dimensions of UF (speed, breakdown, and repair fluency).
An SEM analysis showed that speed fluency was primarily associated with processing speed, while both linguistic resources and processing speed equally contributed to breakdown fluency. Repair fluency was significantly linked to linguistic resources, only when the content of speech is predefined (picture narratives and text retelling speech). Meanwhile, repair fluency was found to be independent of processing speed in all speaking tasks.
