Preschoolers' selective sustained attention and numeracy skills and knowledge

Early numeracy profiles in young children with intellectual disabilities: The role of cognitive functions

Exploring individual differences and looking beyond averaged parameters of early numeracy in young children with mild intellectual disabilities has become an area of interest to many researchers worldwide. This study aimed to identify the different profiles of early numeracy skills in young children with mild intellectual disabilities. For this purpose, we assessed early numeracy through Utrecht early numeracy test and learning aptitude through Detroit Test, in a sample of 135 children diagnosed with intellectual disabilities. The mean of their mental age was 5:09 (years:months). Two-step cluster analysis identified four homogenous groups of children with distinct early numeracy profiles as follows:C1 were fluent in relational and numerical skills up to 20, C2 were fluent in relational skills and numerical skills up to 10, C3 had basic knowledge of relational skills and inconsistent numerical skills up to 10 and C4 had inconsistent relational skills and numerical skills. Results are discussed with reference to their educational implications.

Staying and Returning dynamics of young children's attention

In this paper, we decompose selective sustained attending behavior into components of continuous attention maintenance and attentional transitions and study how each of these components develops in young children. Our results in two experiments suggest that changes in children's ability to return attention to a target locus after distraction ("Returning") play a crucial role in the development of selective sustained attention between the ages of 3.5-6 years, perhaps to a greater extent than changes in the ability to continuously maintain attention on the target ("Staying"). We further distinguish Returning from the behavior of transitioning attention away from task (i.e., becoming distracted) and investigate the relative contributions of bottom-up and top-down factors on these different types of attentional transitions. Overall, these results (a) suggest the importance of understanding the cognitive process of transitioning attention for understanding selective sustained attention and its development, (b) provide an empirical paradigm within which to study this process, and (c) begin to characterize basic features of this process, namely its development and its relative dependence on top-down and bottom-up influences on attention. RESEARCH HIGHLIGHTS: Young children exhibited an endogenously ability, Returning, to preferentially transition attention to task-relevant information over task-irrelevant information. Selective sustained attention and its development were decomposed into Returning and Staying, or task-selective attention maintenance, using novel eye-tracking-based measures. Returning improved between the ages of 3.5-6 years, to a greater extent than Staying. Improvements in Returning supported improvements in selective sustained attention between these ages.

A hidden Markov model for analyzing eye-tracking of moving objects : Case study in a sustained attention paradigm

Eye-tracking provides an opportunity to generate and analyze high-density data relevant to understanding cognition. However, while events in the real world are often dynamic, eye-tracking paradigms are typically limited to assessing gaze toward static objects. In this study, we propose a generative framework, based on a hidden Markov model (HMM), for using eye-tracking data to analyze behavior in the context of multiple moving objects of interest. We apply this framework to analyze data from a recent visual object tracking task paradigm, TrackIt, for studying selective sustained attention in children. Within this paradigm, we present two validation experiments to show that the HMM provides a viable approach to studying eye-tracking data with moving stimuli, and to illustrate the benefits of the HMM approach over some more naive possible approaches. The first experiment utilizes a novel 'supervised' variant of TrackIt, while the second compares directly with judgments made by human coders using data from the original TrackIt task. Our results suggest that the HMM-based method provides a robust analysis of eye-tracking data with moving stimuli, both for adults and for children as young as 3.5-6 years old.

Using a multidimensional model of attention to predict low-income preschoolers' early academic skills across time

The current study examines the organization of attention skills across the preschool year before kindergarten, and tests how distinct attention subcomponents predict early academic skills in a sample of low-income children (n = 99). Children completed well-validated attention tasks in fall at 4.5 years old and spring at 5 years old, capturing the abilities to selectively focus, sustain attention, and employ executive control. Exploratory factor analyses at both time points support a 2-factor model differentiating selective and sustained attention from attention processing speed and executive attention, suggesting that attention in low-income preschoolers may have a simpler organization than the 3-factor structure found in adulthood. Multiple regression models find children's ability to selectively focus and sustain attention serves as a robust concurrent and longitudinal predictor of academic skills. These results highlight the role of selective and sustained attention processes in supporting school readiness for economically vulnerable children.