Мониторинг экономики образования. № 8 (127) Информационный бюллетень. Студенты профессиональных образовательных организаций: высокотехнологичный сегмент СПО.
The paper compares some basic aspects of the national identity of Russian and American students. We have analyzed the views of the students at three leading Russian universities (MSU, MGIMO and NRU HSE) and at Princeton University (USA). The study is based on comparing of Russian students’ positions with those of the Princeton University’s students (USA). The paper consists of two articles. The first article published bellow includes the analysis of the students’ normative perceptions of their countries. The second one is devoted to the aspects of attitudes towards the country that render it an object of national identity (country favoritism, a level of criticism towards the country and a specificity of duty to the country fulfillment)
The aim of the research was to find factors that allow students effectively use Internet. Study consisted of two parts. Questionnaires were filled by 159 1-3 year undergraduate students of NB SU-HSE. Interview was carried out with 7 undergraduate students of NB SU HSE and 7 IT specialists. Questionnaire had three parts: purpose of Internet use; motivation of Internet use (based on inventory by Arestova, Babanin and Voyskunsky); psychological states in the process of using Internet (based on the inventory FPS by Chirkov). Three hypotheses were tested in the study. Hypothesis 1 was confirmed: students' leading motive while using Internet is a cognitive motive and the main goal - search for information. Hypothesis 2 was confirmed by cluster analysis: students experience dysfunctional states while using Internet. Hypothesis 3 was not confirmed: there are no differences in students' and IT specialists' search strategies.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.