Why experts can do what they do: the effects of exogenous resources on the Domain Impact Level of Activities (DILA)

AbstractIn many domains, it is estimated that approximately 10,000 hours of planned learning activities are required to reach an expert level of performance. However, this poses a challenge for learners to balance such extensive learning times with the demands of everyday life. In our study we focused on activities in the domain of chess. We hypothesized that chess-related activities could be better integrated in an individual's life if exogenous resources - specified in the educational capital approach (Ziegler & Baker, 2013) - are sufficiently available. In order to test this hypothesis we introduced the concept of the Domain Impact Level of Activities (DILA), that is, the degree to which a learner's activities are influenced by a certain domain. As expected, we found that the more exogenous resources (educational capital) chess players had at their disposal, the higher was their DILA in regard to social and everyday activities. Concerning social activities, we also found a direct effect of playing time hours and a small indirect effect of educational capital on the DILA via playing time hours. In the model predicting the DILA of everyday activities, these effects were not found. It was concluded that the availability of educational capital facilitates the integration of domain-related activities in a learner's life.Keywords: Educational capital, actiotope, chess, expertiseIn order to attain expertise in a competitive domain like mathematics, music, sports or chess, a person has to spend many hours on practice. Research has clearly shown that the total lifetime amount of practice is related to performance in a variety of domains (Macnamara, Hambrick, & Oswald, 2014). With regard to the particular example of chess, Simon and Chase (1973) claimed that nobody can play on an internationally competitive level "with less than about a decade's intense preparation with the game" (p. 402), which corresponds to approximately 10,000 hours of planned learning (Simon & Chase, 1973a, 1973b). This 10-year rule has proved to be a valid estimation in virtually all domains in which studies have been conducted (e.g., Baker, Cote, & Abernethy, 2003; Ericsson, Krampe, & Tesch-Romer, 1993; Gobet & Campitelli, 2007; Hayes, 1981). For example, Gobet and Campitelli (2007) found in their sample of chess players that, on average, they needed 11,053 hours of deliberate practice in order to reach master level. The slowest player needed as much as 23,608 hours of deliberate practice. Thus, it is safe to conclude that a significant amount of time is needed to become an expert, whereby the aforementioned time estimations only relate to serious training hours. In fact, experts would have spent much more time on activities related to their domain of expertise. These include domainspecific activities not intended for improvement (and thus not accounted for in the deliberate practice assessments; e.g. Gobet & Campitelli, 2007), such as, commuting to the training venue, passively enjoying the domain (e.g., a music expert listening to music, a sports expert watching sports events, or a sculptor visiting art exhibitions), or talking about the domain with friends and family.Time management demands in chessChess expertise is for a number of reasons an appropriate focus to address the question of how time demands can be met by future chess experts. First, chess has already attracted many research studies so that it has now a reputation as the "drosophila of cognitive psychology" (Grabner, Stern, & Neubauer, 2007). It might be the domain for which we have most data available and that is currently best understood. Secondly, expertise levels are quantifiable through a valid rating system (Elo, 1986; Hambrick et al., 2014). Thirdly, from a practical perspective the access to a larger number of experts, which is important for such research, is relatively easy. Finally, the highly motivating character of the game makes it especially suited for the study of our research aim. …