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Cognitive modeling studies in adults have established that visual working memory (WM) capacity depends on the representational precision, as well as its variability from moment to moment. By contrast, visuospatial WM performance in children has been typically indexed by response accuracy—a binary measure that provides less information about precision with which items are stored. Here, we aimed at identifying whether and how children’s WM performance depends on the spatial precision and its variability over time in real-world contexts. Using smartphones, 110 Grade 3 and Grade 4 students performed a spatial WM updating task three times a day in school and at home for four weeks. Measures of spatial precision (i.e., Euclidean distance between presented and reported location) were used for hierarchical modeling to estimate variability of spatial precision across different time scales. Results demonstrated considerable within-person variability in spatial precision across items within trials, from trial to trial and from occasion to occasion within days and from day to day. In particular, item-to-item variability was systematically increased with memory load and lowered with higher grade. Further, children with higher precision variability across items scored lower in measures of fluid intelligence. These findings emphasize the important role of transient changes in spatial precision for the development of WM.
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.
The effects of aging on response time were examined in a paper-based lexical-decision experiment with younger (age 18–36) and older (age 64–75) adults, applying Ratcliff’s diffusion model. Using digital pens allowed the paper-based assessment of response times for single items. Age differences previously reported by Ratcliff and colleagues in computer-based experiments were partly replicated: older adults responded more conservatively than younger adults and showed a slowing of their nondecision components of RT by 53 ms. The rates of evidence accumulation (drift rate) showed no age-related differences. Participants with a higher score in a vocabulary test also had higher drift rates. The experiment demonstrates the possibility to use formal processing models with paper-based tests.