Over 25 years ago Ericsson et al. (1993) published the results of their search for the most effective forms of training in music, a domain where knowledge of effective training has been accumulated over centuries. At music academies master teachers provide students individualized instruction and help them identify goals and methods for their practice sessions between meetings – this form of solitary practice was named deliberate practice, and its accumulated duration during development was found to distinguish groups with differing levels of attained music performance. In an influential meta-analysis Macnamara et al. (2014) identified studies that had collected estimates of practice accumulated during development and attained performance and reported that individual differences in deliberate practice accounted for only 14% of variance in performance. Their definition of “deliberate practice” differs significantly from the original definition of deliberate practice and will henceforth be referred to as structured practice. We explicate three criteria for reproducible performance and purposeful/deliberate practice and exclude all effect sizes considered by Macnamara et al. (2014) that were based on data not meeting these criteria. A reanalysis of the remaining effects estimated that accumulated duration of practice explained considerably more variance in performance (29 and 61% after attenuation correction). We also address the argument that the limited amount of variance explained by the duration of practice necessarily implies an important role of genetic factors, and we report that genetic effects have so far accounted for remarkably small amounts of variance – with exception of genetic influences of height and body size. The paper concludes with recommendations for how future research on purposeful and deliberate practice can go beyond recording only the duration of practice to measuring the quality of practice involving concentration, analysis, and problem solving to identify conditions for the most effective forms of training.
This study developed and empirically tested a model to predict the factors affecting students’ behavioral intentions toward using mobile learning (m-learning). This study explored the behavioral intention to use m-learning from the perspective of consumers by applying the extended unified theory of acceptance and use of technology (UTAUT) model with the addition of perceived enjoyment, mobile self-efficacy, satisfaction, trust, and perceived risk moderators. A cross-sectional study was conducted by employing a research model based on multiple technology acceptance theories. Data were derived from an online survey with 1,562 respondents and analyzed using structural equation modeling. Partial least squares (PLS) regression was used for model and hypothesis testing. The results revealed that (1) behavioral intention was significantly and positively influenced by satisfaction, trust, performance expectancy, and effort expectancy; (2) perceived enjoyment, performance expectancy, and effort expectancy had positive associations with behavioral intention; (3) mobile self-efficacy had a significantly positive effect on perceived enjoyment; and (4) perceived risk had a significantly negative moderating effect on the relationship between performance expectancy and behavioral intention. Our findings correspond with the UTAUT model and provide a practical reference for educational institutions and decision-makers involved in designing m-learning for implementation in universities.