Between PIRLS and PISA: The advancement of reading literacy in a 10–15-year-old cohort
While reading literacy in Russian 10-year-old schoolchildren was exceptionally high in the PIRLS assessment, reading literacy of 15-year-old students as measured by PISA stayed low. To elucidate this controversy, we developed the“Push–Pull”diagnostic method combining PIRLS and PISA approaches. This new tool compares reading literacy across at leastfive years of schooling. With Push–Pull, we assessed grades 4, 6 and 9 (3110 students) and demonstrated that two years of study in Russian middle school (grades 5 and 6) failed to pro-mote students' ability to comprehend informational texts, bringing modest improvement overfive years of schooling. By measuring and monitoring the dynamics of reading literacy, Push–Pull spots the dead ends of Russian educational approach to reading and comprehension of informational texts in 10–15-year-old readers.
The authors estimate contribution of different factors in reading skills of 15?year-olds by using four models of multilevel regression analysis. It turned out that the most significant factor is family background — not only at the individual level, but at the school level as well (average school socio-economic status of schoolchildren families effects average reading skills). At the school level the aggregated family characteristics of students affect individual achievements, and this effect surpasses an effect of school resources and localization of schools — those school factors that show a significant contribution to achievement. Attitudes toward reading and learning are significant at the individual level, but at the school level children’s attitudes toward reading and school don’t make an independent contribution to the individual results.
On the basis of PISA-2009 materials: Reading literacy The efficiency of one year of study was explored on the basis of PISA-2009 (reading) materials in seven countries: Russia, the Czech Republic, Hungary, Slovakia, Germany, Canada and Brazil. An instrumental variable was used, which enabled to assess the effect of one year of study by the nonstrict method of regression discontinuity. The analysis included both general educational programs and vocational educational programs together and comprehensive schools separately. It is found that in Russia the efficiency of one year of study is insignificant to all programs’ students. In the countries where early division into general educational and vocational programs is practised, the efficiency of studying is lower than in the countries where all pupils of 15 years old learn a general educational program. For general educational programs’ students the efficiency of studying is significant in all countries. Compared to the general educational trajectory, low efficiency is typical of vocational programs’ students. The way a family’s socio-economic status and efficiency of school education are interrelated and how much they are interrelated depends a lot on an educational system and vary widely by country. In Russia, as well as in some other countries, efficiency of studying does not depend on pupils’ socio-economic indices. The importance of the results obtained for assessment of efficiency of studying is discussed, and particularly for fair assessment of national achievements in countries with different sets of educational trajectories.
The Programme for International Student Assessment (PISA) is a worldwide study by the Organisation for Economic Co-operation and Development (OECD) in member and non-member nations of 15-year-old school pupils' scholastic performance on mathematics, science, and reading. It was first performed in 2000 and then repeated every three years. It is done with view to improving education policies and outcomes. The data has increasingly been used both to assess the impact of education quality on incomes and growth and for understanding what causes differences in achievement across nations.
The article presents the results of a further multidimensional analysis of PIRLS"2006 data on the Russian sample. In the first part, the author discusses research on the connection between various characteristics of the school and family and the childs achievements in PIRLS. In particular, she demonstrates that children from different socio" demographic groups showed a non"uniform five year long dynamic of achievements. The conditions under which school resources begin to have an impact on students reading skills are determined. The author suggests optimal combinations of reading tasks and text comprehension tasks. The second part describes the procedure and results of a regression analysis of key variables relating to school and home learning environments. The conclusion is that school and family factors have an unequal impact on the reading skills of a child. A negative impact of certain factors on reading skills is shown. The author proceeds to discuss alternative interpretations of the results and the desirability of secondary analyses of international surveys.
This publication presents Russia results in PISA 2018. It also shows the dynamics of PISA scores in the 2000-s. The changes in different types of reading skills are presented as well as the proportion of functionally illiterate students. Besides the scores, the data that describes schools climate, including attitude to school, bullying, discipline in class, are analysed. Some issues related to the provision of schools with resources are being addressed.In addition, the social and territorial inequality of educational outcomes in Russia is described. In particular, PISA 2018 allows us to compare the results of the Moscow region and the Republic of Tatarstan with the average scores in the country. Based on the analysis, authots make basic hypothesis about possible changes in Russian education that can be associated with Russia results in PISA. At the end, the publication proposes some steps that could help to improve educational outcomes of Russian students. The publication will be interesting to a wide audience of specialists engaged in educational policy and practice, as well as to researchers of educational inequality and education quality factors.
Using a natural experiment situation, this chapter describes the process of curriculum reform in Russian-medium schools in Latvia and Estonia. The research question focuses on whether those curriculum reforms were successful from the perspective of schools’ interiorisation of new curriculum and PISA (Programme for International Student Assessment) performance improvement. Using the three-layered curriculum approach (intended, implemented and attained curriculum), this chapter analyses how the intentions of the laws and other reform-related documents were implemented in everyday school practice and are reflected in attained educational results. To address this issue, a series of in-depth interviews in Russian-medium schools, in conjunction with the PISA 2003 2012 trends analysis, were conducted. The results showed that intended and attained curricula have grown closer in both countries. Schools actively implement proposed reforms in teaching, and PISA performance has been constantly improving, showing that the attained curriculum is approaching what was intended, though this process is different in the two countries.
The Programme for International Student Assessment (PISA) is an influential worldwide study that tests the skills and knowledge in mathematics, reading, and science of 15-yearold students. In this paper, we show that PISA scores of individual students can be predicted from their digital traces. We use data from the nationwide Russian panel study that tracks 4,400 participants of PISA and includes information about their activity on a popular social networking site. We build a simple model that predicts PISA scores based on students’ subscriptions to various public pages on the social network. The resulting model can successfully discriminate between low- and high-performing students (AUC = 0.9). We find that top-performing students are interested in pages related to science and art, while pages preferred by low-performing students typically concern humor and horoscopes. The difference in academic performance between subscribers to such public pages could be equivalent to several years of formal schooling, indicating the presence of a strong digital divide. The ability to predict academic outcomes of students from their digital traces might unlock the potential of social media data for large-scale education research.
The quality of education in the United States has been heavily criticized in part because of U.S. students’ performance on international tests, such as the Program for International Student Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS). Although simple country averages may support such criticisms, there are many problems in comparing test scores of students in the U.S. as a whole with students in countries with very different social and educational environments. Not least of these problems is that students in the United States do not attend school in a “U.S. educational system,” but rather in at least 51 different systems, many of which have experienced very significant progress over time. The most relevant lessons for improving U.S. education may therefore be found in our successful states, rather than in other countries.
Institutions affect investment decisions, including investments in human capital. Hence institutions are relevant for the allocation of talent. Good market-supporting institutions attract talent to productive value-creating activities, whereas poor ones raise the appeal of rent-seeking. We propose a theoretical model that predicts that more talented individuals are particularly sensitive in their career choices to the quality of institutions, and test these predictions on a sample of around 95 countries of the world. We find a strong positive association between the quality of institutions and graduation of college and university students in science, and an even stronger negative correlation with graduation in law. Our findings are robust to various specifications of empirical models, including smaller samples of former colonies and transition countries. The quality of human capital makes the distinction between educational choices under strong and weak institutions particularly sharp. We show that the allocation of talent is an important link between institutions and growth.