Thesis

coincide with improvements in others. This also suggests that taking a comprehensive view on a student’ skill set can be valuable for identifying effective strategies to address skill deficits. This chapter builds upon the literature on the self-productivity and cross-fertilization of skills. The term ‘self-productivity’ of skills was coined by Cunha and Heckman (2007). It embodies the concept that the stock of skills in one period increases the stock of skills in subsequent periods. Whereas the self-productivity of skills refers to the role of a skill in its accumulation, cross-fertilization refers to the role of a skill in the accumulation of other skills. In this context, the relationship between language and math skills has been subject of investigation in recent literature. The Pathways to Mathematics model of LeFevre et al. (2010) recognizes the importance of linguistic abilities for the development of math skills. Supporting this view, several studies identify mathematical language, for instance, as a way to explain how language skills contribute to mathematical growth (e.g., Purpura & Logan, 2015; Toll & Van Luit, 2014). In a related line of research, Sarnecka and Gelman (2004) show how young children use numerosities to understand number words, thereby intertwining language and math skills. Similarly, Vukovic and Lesaux (2013) acknowledge the role of general verbal ability and phonological skills for numerical reasoning and arithmetic problem-solving, respectively. Other research further clarifies which language skills predict mathematical skills and how they do so (e.g., Chow & Ekholm, 2019; Grimm, 2008; Hecht et al., 2001; Jordan et al., 2003; Krajewski & Schneider, 2009; LeFevre et al., 2010). Whereas language skills seem important to develop math skills, the literature also reports findings on the reverse (e.g., Claessens & Engel, 2013; Erbeli et al., 2021; Purpura et al., 2017). 81

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