The Ecological System of the Digital Educational Environment as A New Definition of Modern Education in the View of Teachers

Digital technologies and products are a new reality of modern education, but the degree of their influence on the ecology of the digital educational environment has not been fully studied. The article examines teachers' ideas about a new definition of education - the ecology of the digital educational environment; about the impact of digital educational products on the cognitive, personal and activity sphere of students. Implement the tasks set, an anonymous online survey of teachers of secondary schools in Moscow, the Moscow region, Voronezh, Nizhny Novgorod, Samara was conducted using the Google form. The article, based on the analysis of teachers' ideas about the ecology of the digital educational environment, risk zones and their impact on the cognitive, personal and activity spheres of students are identified; criteria for assessing the impact of digital educational products on cognitive processes, personal qualities and motivation of students learning activities are determined; indicators for each type of criteria are considered. The article shows, in the view of teachers, digital educational products have an ambivalent impact on the development of a student: they act as a resource, a means of development, and at the same time, they are risky for the development of a student

The Irrecoverable Loss in Sleep on Weekdays of Two Distinct Chronotypes Can Be Equalized by Permitting a >2 h Difference in Waking Time

Background: Our work/study culture is biased towards the circadian clocks of “morning types”, whereas “evening types” are forced to advance their weekday waking times relative to weekend waking times. Since the experimental research consistently reveals a >2 h difference between these two chronotypes in the positions of their endogenous circadian phases, we hypothesized the necessity to permit a >2 h difference between them in weekday waking times to equalize their irrecoverable loss in sleep on weekdays. Methods: A total of 659 and 1106 participants of online surveys identified themselves as morning and evening types, respectively. The hypothesis was tested by applying a model of sleep–wake regulation for simulating sleep times reported by 245 lecturers of these two types, and by comparison of sleep times of these types among these lecturers and 1520 students. Results: The hypothesis was supported by results showing that, if, on weekdays, an “average” morning type wakes at 6 a.m., the equalization of the weekday sleep loss of the two chronotypes would require the waking time of an “average” evening type to be no earlier than 8 a.m. Conclusions: These results may be implemented in a model-based methodology for the correction of weekday waking times to equalize weekday sleep loss