Deutsches Institut für Internationale Pädagogische Forschung (DIPF)
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- Delay of gratification (1)
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The ability to delay gratification, to wait for a larger but delayed reward in the presence of a smaller but constantly available reward, has been shown to be predictive for various aspects of everyday life. For instance, preschool children who were better able to delay gratification achieved better school grades, a higher education, a better ability to cope with stress, as well as a reduced risk for being overweight or consume drugs up to 30 years later (Mischel et al., 2011). However, despite the importance of delay of gratification cognitive factors underlying individual differences are only poorly understood. Wittmann and Paulus (2008) suggested that individuals who overestimate the duration of time intervals experience waiting times as more costly and are, therefore, less likely to delay gratification. Furthermore, a recent study revealed an association between less accurate internal clock speed and a behavioral choice delay task (Corvi, Juergensen, Weaver, & Demaree, 2012). Further evidence for an association between temporal processing and delay of gratification can be derived from studies using clinical samples. For instance, children with attention-deficit/hyperactivity disorder (ADHD) consistently prefer smaller, immediate rewards over larger, delayed rewards and show impaired temporal processing (Sonuga-Barke, Bitsakou, & Thompson, 2010). However, no study has directly tested an association between a measure of temporal processing and a classical delay of gratification task in children with and without ADHD so far.
As part of a larger study, 64 children (29 with ADHD) aged between 8 to 12 years performed a version of an auditory duration discrimination task and a delay of gratification task. In the duration discrimination task, the children were presented with two unfilled intervals indicated by two brief tones each. The baseline interval lasted for 400 ms, while the comparison interval was always longer and adjusted up or down in 10 ms steps securing an accuracy of 80%. In the delay of gratification task, the children were instructed that they could either opt for one chocolate bar immediately or that they could wait to receive two chocolate bars. Unbeknownst to the children, the waiting time lasted 25 minutes but children were told that they could decide for the immediate chocolate bar at any time by ringing a bell.
Children with ADHD did not differ in their performance from children without ADHD in the duration discrimination task or the delay of gratification task. However, in the whole sample of children with and without ADHD, children who waited for the additional chocolate bar showed a better duration discrimination than children who failed to wait for the additional chocolate bar [t(62) = -2.52, p = .01].
We demonstrated an association between temporal processing ability and the ability to delay gratification. These results need to be replicated in further studies with larger sample sizes. Moreover, different tasks measuring temporal processing and delay of gratification should be used to further clarify the relationship of temporal processing, delay of gratification, and ADHD.
Based on a meta-analysis, Redick and Lindsey (2013) found that complex span and n-back tasks show an average correlation of r = 0.20, and concluded that "complex span and n-back tasks cannot be used interchangeably as working memory measures in research applications" (p. 1102). Here, we comment on this conclusion from a psychometric perspective. In addition to construct variance, performance on a test contains measurement error, task-specific variance, and paradigm-specific variance. Hence, low correlations among dissimilar indicators do not provide strong evidence for the existence, or absence, of a construct common to both indicators. One way to arrive at such evidence is to fit hierarchical latent factors that model task-specific, paradigm-specific, and construct variance. We report analyses for 101 younger and 103 older adults who worked on nine different working memory tasks. The data are consistent with a hierarchical model of working memory, according to which both complex span and n-back tasks are valid indicators of working memory. The working memory factor predicts 71% of the variance in a factor of reasoning among younger adults (83% for among older adults). When the working memory factor was restricted to any possible triplet of working memory tasks, the correlation between working memory and reasoning was inversely related to the average magnitude of the correlations among the indicators, indicating that more highly intercorrelated indicators may provide poorer coverage of the construct space. We stress the need to go beyond specific tasks and paradigms when studying higher-order cognitive constructs, such as working memory.
Background: Recent studies have suggested substantial fluctuations of cognitive performance in adults both across and within days, but very little is known about such fluctuations in children. Children's sleep behavior might have an important influence on their daily cognitive resources, but so far this has not been investigated in terms of naturally occurring within-person variations in children's everyday lives.
Methods: In an ambulatory assessment study, 110 elementary school children (8–11 years old) completed sleep items and working memory tasks on smartphones several times per day in school and at home for 4 weeks. Parents provided general information about the children and their sleep habits.
Results: We identified substantial fluctuations in the children's daily cognitive performance, self-reported nightly sleep quality, time in bed, and daytime tiredness. All three facets were predictive of performance fluctuations in children's school and daily life. Sleep quality and time in bed were predictive of performance in the morning, and afternoon performance was related to current tiredness. The children with a lower average performance level showed a higher within-person coupling between morning performance and sleep quality.
Conclusions: Our findings contribute important insights regarding a potential source of performance fluctuations in children. The effect of varying cognitive resources should be investigated further because it might impact children's daily social, emotional, and learning-related functioning. Theories about children's cognitive and educational development should consider fluctuations on micro-longitudinal scales (e.g., day-to-day) to identify possible mechanisms behind long-term changes.
Reaction times to previously ignored information are often delayed, a phenomenon referred to as negative priming (NP). Rothermund et al. (2005) proposed that NP is caused by the retrieval of incidental stimulus-response associations when consecutive displays share visual features but require different responses. In two experiments we examined whether the features (color, shape) that reappear in consecutive displays, or their level of processing (early-perceptual, late-semantic) moderate the likelihood that stimulus-response associations are retrieved. Using a perceptual matching task (Experiment 1), NP occurred independently of whether responses were repeated or switched. Only when implementing a semantic-matching task (Experiment 2), negative priming was determined by response-repetition as predicted by response-retrieval theory. The results can be explained in terms of a task-dependent temporal discrimination process (Milliken et al., 1998): Response-relevant features are encoded more strongly and/or are more likely to be retrieved than irrelevant features.
The approximate number system (ANS) has been consistently found to be associated with math achievement. However, little is known about the interactions between the different instantiations of the ANS and in how many ways they are related to exact calculation. In a cross-sectional design, we investigated the relationship between three measures of ANS acuity (non-symbolic comparison, non-symbolic estimation and non-symbolic addition), their cross-sectional trajectories and specific contributions to exact calculation. Children with mathematical difficulties (MD) and typically achieving (TA) controls attending the first six years of formal schooling participated in the study. The MD group exhibited impairments in multiple instantiations of the ANS compared to their TA peers. The ANS acuity measured by all three tasks positively correlated with age in TA children, while no correlation was found between non-symbolic comparison and age in the MD group. The measures of ANS acuity significantly correlated with each other, reflecting at least in part a common numerosity code. Crucially, we found that non-symbolic estimation partially and non-symbolic addition fully mediated the effects of non-symbolic comparison in exact calculation.