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Developing communicative competence: a longitudinal study of the acquisition of mental state terms and indirect requests*

Published online by Cambridge University Press:  29 September 2014

HANNAH DE MULDER*
Affiliation:
Utrecht Institute of Linguistics OTS, University of Utrecht, the Netherlands
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Abstract

This longitudinal study involving 101 Dutch four- and five-year-olds charts indirect request (IR) and mental state term (MST) understanding and investigates the role that Theory of Mind (ToM) and general linguistic ability (vocabulary, syntax, and spatial language) play in this development. The results showed basic understanding of IR and MST in four-year-olds, but full understanding had not been reached even at five years old. Furthermore, although ToM predicted both IR and MST when linguistic ability was not taken into account, this relationship was no longer significant once the language measures were added. Linguistic ability thus seems to play an important role in the development of both IR and MST. Additional analyses revealed that whereas syntactic ability was the primary predictor of IR, spatial language was the best predictor of MST, suggesting that IR relies primarily on general linguistic skills, but that more specific aspects of language may bootstrap MST.

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Copyright © Cambridge University Press 2014 
Figure 0

Table 1. Means, standard deviations, and ranges of all the tests at the first and second time-point

Figure 1

Table 2. Predicting mental state term understanding at time 2 from ToM and language at time 1

Figure 2

Fig. 1. Scatterplot: ToM (time1), Reynell (time1), and mental state term understanding (MST) (time2).

Figure 3

Table 3. Predicting ToM at time 2 from mental state term understanding at time 1

Figure 4

Table 4. Predicting indirect requests at time 2 from ToM and language at time 1

Figure 5

Fig. 2. Scatterplot: ToM (time1), Reynell (time1), and indirect request understanding (IR) (time2).

Figure 6

Table 5. Predicting mental state terms at time 2 from ToM, spatial, and non-spatial language at time 1

Figure 7

Table 6. Predicting indirect requests at time 2 from ToM, spatial, and non-spatial language at time 1