The purpose of the article is to draw the attention of the authors and readers of the journal to the problem of using artificial intelligence in higher education and science. The article consists of two interrelated parts. In the first part, authors of the article discuss the case of using ChatGPT for graduate writing in terms of implications for higher education. In the second part, the authors turn to the reaction of the academic community to the emergence of generative artificial intelligence and consider its shortcomings and opportunities for education and science. In conclusion, authors of the present work invite readers to an academic discussion about artificial intelligence in higher education and science on the pages of our journal.
The article presents the results of the All-Russian sociological study of academic and sociocultural adaptation of students in Russian universities. The purpose of the article was to identify and interpret the problems of students’ adaptation to the educational process, research activities, project training, sociocultural environment of the university. The subject of the study was the selfassessment of the adaptability of junior students, as well as the factors influencing it. The novelty of the research consists in a comprehensive consideration of students’ adaptation to key activities at the university, including a new type of project activity. The empirical study was implemented through a massive online survey of students in May-July 2022. The respondents were first and second-year students enrolled in bachelor’s and full-time specialty programs in various areas of training. The total volume of the sample was 15,902 people, the maximum sampling error didn’t exceed 1%.Based on empirical data, the article shows the main problems of students’ adaptation to learning, namely, a significant amount of new information, the pace of the educational process, the format of practical classes and coursework that require more independence and activity than in school education. The authors reveal the connection between the level of students’ educational activity and initiative and the degree of their integration into the university community. The negative trend of decreasing student activity in the research field compared to the school period of study , as well as the preservation of a high proportion of those who are prone to academic fraud due to the lack of adaptive resources, is shown. It is concluded that the adaptation of students to project activities is complicated by their unwillingness to responsibility and independence, an attitude towards individualism and autonomy, an insufficiently high level of professional culture and professional knowledge, which is at odds with the expectations of project customers. At the same time, positive effects have been recorded in the field of sociocultural adaptation of nonresident and foreign students. Getting used to the specifics of Russian culture, the academic environment, and the new urban society occurs without much difficulty. The conclusion is made about the effectiveness of university programs of adaptation and support of foreign students and students with disabilities, reasoned by the absence of significant differences in adaptation problems in all groups of students.
Data science as an emerging branch of applied knowledge and a new field of study is showing a strong momentum. Besides, the corresponding sphere of educational research is actively developing. At the same time, most of the scientific publications are aimed at studying specific issues related to the content of the programs and their methodological support. The wider context and especially the international perspective are lacking for the necessary attention of researchers.In this regard, the purpose of our study was to summarize and systematize information about training programs in the field of data science presented on online platforms of the main macro-regions – America, Europe and Asia. For this purpose, we found out what elements the corpus of data science training programs consists of, as well as how courses are distributed on educational platforms by countries, organizational providers, level of education and duration of study. Based on the data obtained, we conducted a comparative interregional study of educational programs presented on online platforms.The findings made it possible to draw conclusions about the specifics of the global landscape of data science online education, as well as to determine the specifics of the Russian segment and to formulate recommendations for solving significant problems of the domestic economy using data science online education.
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