Sleep Patterns in Elementary School Children (Grades 2-5) and Adolescents (Grade 10)

Background: To date, there is limited research examining sleep patterns in elementary school children. Previous researchers focused on parental responses rather than student responses to determine factors that affect sleep. The presented study surveyed sleep patterns and examined external factors affecting total sleep time among elementary school children and adolescents. Methods: Students in grades 2-5 (n=885) and grade 10 (n=190) enrolled in a public school system in the Northeast, completed a district administered survey that included questions on sleep duration and hygiene. Results. Average reported sleep duration decreased with increasing grade level. Children in grades 2-5 woke up earlier (31.7-72.4%) and on their own in comparison to adolescents in grade 10 (6.8%). Significantly shorter sleep durations were associated with having a television (grades 2, 4, 5, p< 0.01) or a cell phone in the room (grades 3, 4; p < 0.05), playing on the computer or video games (grades 3, 4, p<.001) before going to bed. In contrast, students in grade 2, 3, & 4 who reported reading a book before going to bed slept on average 21 minutes more per night (p=.029, .007, .009, respectively). For tenth graders, only consumption of energy drinks led to significant reduction in sleep duration (p<.0001). Conclusion. Sleep is a fundamental aspect in maintaining a healthy and adequate life style. Understanding sleep patterns will assist parents, health care providers, and educators in promoting quality sleep hygiene in school-aged children.

Self-Organizing Grammar Induction Using a Neural Network Model

This paper presents a self-organizing, real-time, hierarchical neural network model of sequential processing, and shows how it can be used to induce recognition codes corresponding to word categories and elementary grammatical structures. The model, first introduced in Mannes (1992), learns to recognize, store, and recall sequences of unitized patterns in a stable manner, either using short-term memory alone, or using long-term memory weights. Memory capacity is only limited by the number of nodes provided. Sequences are mapped to unitized patterns, making the model suitable for hierarchical operation. By using multiple modules arranged in a hierarchy and a simple mapping between output of lower levels and the input of higher levels, the induction of codes representing word category and simple phrase structures is an emergent property of the model. Simulation results are reported to illustrate this behavior.