Abstract. In this paper we explore motivational structure of students taking a challenging university course. The participants were second-year undergraduate students majoring in Economics, Sociology, Management and Humanities, enrolled in the Data Science minor. Using expectancy-value theory as a framework, we aim (1) to analyze gender differences in motivation; (2) to identify the link between the components of motivation and academic achievement; (3) to estimate the role of the previous academic achievement and educational choices. Two alternative theoretical models are proposed and tested on empirical data. Structural equation modeling (SEM) in MPlus 7.31 was used for analysis. We found that the course is more popular among males students, who also demonstrate higher level of expectancy for success. However, there is no gender difference in academic performance. Students majoring in Sociology and Economics perceive Data Science as more interesting and useful than Management and Humanities students. SEM analysis empirically validated the model in which expectancy of success directly influences academic achievement, and values influence is mediated by expectancies. The final model that includes motivation, gender, student's major, and previous achievement explains 34% of variance in academic performance. We discuss the role of different components of student motivation and practical significance of our results.
Александров Даниил Александрович - кандидат биологических наук, заведующий научно-учебной лабораторией «Социология образования и науки» Национального исследовательского университета «Высшая школа экономики» (Санкт-Петербург). E-mail: dalexandrov@hse.ruИванюшина Валерия Александровна - кандидат биологических наук, ведущий научный сотрудник научно-учебной лаборатории «Социология образования и науки» Национального исследовательского университета «Высшая школа экономики» (Санкт-Петербург). E-mail: ivaniushina@hse.ruСимановский Дмитрий Леонидович - аспирант Национального исследовательского университета «Высшая школа экономики» (Санкт-Петербург). E-mail: simanogi@gmail.comАдрес: 190008, Санкт-Петербург, ул. Союза Печатников, 16Под цифровым барьером первого уровня понимается различие в доступе к интернету у разных групп населения, цифровой барьер второго уровня — это различия в практиках использования интернета. Эмпирической базой исследования являются опросы школьников, выполненные в 2014–2016 гг. в СанктПетербурге (94 школы, 3739 учеников 10‑х и 11‑х классов) и в Калужской области (249 школ, 27 904 ученика 6–9‑х классов). Показано, что в мегаполисе цифровой барьер первого уровня отсутствует. В Калужской области различия в доступе к интернету обусловлены типом населенного пункта (город или село), составом семьи (полные или неполные семьи) и образованием родителей школьника (наличие или отсутствие высшего образования); в самом уязвимом положении оказываются школьники, социальноэкономическое положение которых характеризуется совпадением всех трех негативных факторов. Что касается использования интернета, то ни в Калужской области, ни в Санкт-Петербурге не выявлено различий между школьниками в зависимости от семейного бэкграунда, тапа школы, типа населенного пункта. Большинство школьников пользуются образовательными ресурсами, причем интенсивность использования увеличивается с возрастом. Описаны несколько специализированных образовательных ресурсов для школьников. Наиболее популярным ресурсом является Википедия; из специализированных ресурсов школьники чаще всего пользуются сайтом Znanija.com. Лишь небольшой процент школьников (около 2%) пользуются сайтами готовых домашних заданий.
Abstract. The present study examines structural and socio-psychological factors affecting attitudes towards quitting the profession among school teachers. We explore effects of perceived workplace difficulties, employment opportunities, self-efficacy beliefs, and emotional attachment to the teaching profession. The survey was conducted among public secondary school teachers in Saint Petersburg, Russia (N = 730). The regression analysis revealed that self-efficacy beliefs and professional commitment are the strongest predictors for retention, some work-related stress factors contribute to the likelihood of switching profession, while the number of years of teaching experience and work experience outside of teaching have no effect. The results do not support the hypothesis that early-career teachers are more tolerant to switching professions. The implications for retaining teachers in the profession are discussed.
School tracking is defined as the placement of students into different school types, structured hierarchically by performance. In the majority of OECD countries, tracking takes place at the age of 15 or 16. In Russia, similarly, students are sorted into "academic" (high school) and "non-academic" (vocational training) tracks after Grade 9, at the age of 15. However, even before that split, Russian children are distributed among schools of differing types ("regular" schools, specialized schools, gymnasiums and lyceums), which some researchers refer to as "pre-tracking" . No empirical evidence as to how often students change school prior to formal tracking at age 15 has been available so far. Using the St. Petersburg administrative school database containing information on all school transitions made in the 2014/15 academic year, this article investigates school mobility among first-to eleventh-graders. In particular, it compares the frequency of changing school across different grades as well as the overall incidence of school transitions. Regression models were constructed for academic/non-academic track choice after Grade 9, which link the share of students transitioning to vocational training institutions with school characteristics. With regard to changing school prior to formal tracking, findings reveal rather low school mobility. Indeed, in spite of having vast school change opportunities in a school system of a Russian megalopolis, 65% of students attend the same school from Grade 1 through Grade 9, and 85% stick to one school between Grades 5 and 9. This is consistent with Yulia Kosyakova and her co-authors' inferences on pre-tracking in the Russian secondary school. The implications for building individual educational trajectories and dealing with educational inequality are discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.