09 SES 01 C, Investigating Relations of Student, School and Context Variables With Students’ Attitudes, Behaviors and Academic Performance
The paper uses pupil level figures to analyze determinants of school repetition in Rio de Janeiro public schools. This is a worldwide phenomenon that presents significant variation among educational systems. We define school repetition or failure as an educational outcome that prevents the pupil to move forward to the next grade. This decision happens at the end of each school year.
In Brazil, school failure has been declining since the beginning of 1990s, however, the figures are still considered high when compared to other countries in the region – South America. In 2012, Brazil presented the fifth highest rate among all PISA participants. In the case of Rio de Janeiro, the rates have been increasing since 2007 (Crahay; Baye, 2013). It is possible to observe two transitions where pupils are more likely to fail – 3rd to 4th grade, eight year old pupils, and 5th to 6th grade, eleven-year-old pupils. More recent data from 2014, shows that around one quarter of all pupils enrolled in 3rd grade in Rio public schools were retained at the end of the school year. For the 6th grade, around 18% were retained and obligated to attend the same grade in the following year.
The subject of school repetition has been a concern for educational researchers in Brazil for at least 30 years. Nonetheless, very few studies have analyzed, with robust designs, the effects of repetition on pupils´ academic trajectory and, more importantly, the determinants that can help predict the phenomena (Riani; Silva; Soares, 2012). Which variables are associated with school failure? This study will consider pupil and school level variables to analyze the phenomenon using a longitudinal model.
There is one main argument used by teachers and educational researchers in order to justify the need to hold back pupils at the end of a school year. The rationale suggests that these pupils have not learned what was expected for each particular grade. In this way, it would be necessary, and even beneficial, for the pupils to have a second chance to learn and consolidate the subjects. There is an idea that allowing the pupil to progress without knowing the subjects can be even more harmful.
However, more recent and robust studies analyzing the impact of school failure suggest that this practice is not associated with an increase pupils’ academic achievement. In fact, there is some evidence suggesting that repetition is associated with a decline in academic performance. Not only that, facing school failure increases the chances of a second repetition or school dropout (Hattie, 2009; Manacorda, 2006; 2012).
Many cities in Brazil, including Rio de Janeiro, present high proportion of pupils with multiple school failures. As an example, in 2014, considering all pupils enrolled from 1st to 9th grades – pupils from 6 to 14 years old – in Rio public schools, around half had experienced at least one school failure and around 20% two or more school failures. This particular scenario creates an additional problem. It would not be unlikely to observe pupils with very different ages studying in the same classroom. The age difference is described by teacher, head teacher, principals and even parents as a problem to “classroom climate”. To deal with this situation, many educational systems in Brazil have created “special classes” for pupils with some early grade retentions. These classes were intended to provide a better opportunity for those pupils. The concern is that clustering disadvantaged pupils in specific classrooms or schools could create even worst educational opportunities as observed before in the regular classes (Bartholo, 2014).
Bartholo, T. L. School Segregation in Rio de Janeiro Public Schools: Causes and Consequences. PhD Thesis: Federal University of Rio de Janeiro, 2014. Crahay, M. & Baye, A. (2013) Existem escolas justas e eficazes? Esboço de resposta baseado no PISA 2009. Cadernos de Pesquisa, v.43 n.150 p.858-883. Diggle. P. J. The analysis of Longitudinal Data. Oxford Statistical Science series. Oxford University Press, 2001. Goldstein, H. Multilevel Statistical Models. Kendall’s library of statistics; 3.Arnold London, 2003. Hattie, J. Visible Learning for Teachers. Routledge: New York, 2009. Manacorda, M. Grade Failure, Drop out and Subsequent School Outcomes: Quasi –Experimental Evidence form Uruguayan Administrative Data. In: Centre for the Economics of Education Seminar, 13 Dec 2006, London, UK. ftp://www.cemfi.es/pdf/papers/wshop/Manacorda.pdf ________. The cost of Grade Retention. The Review of Economics and Statistics, v. 94, n.2, May, 2012, p. 596-606. Riani, J. L. R.; Silva, V. C. & Soares, T. M. Reapeating or advancing? An analysis of school failure in public schools of Minas Gerais. Educação e Pesquisa, São Paulo, v. 38, n. 03, p. 623-636, jul-set., 2012. http://www.scielo.br/pdf/ep/v38n3/en_06.pdf Singer, J. D. Willet, J. B. Applied Longitudinal Data Analyysis: Modeling Change and Ocurrence. Oxford University Press, New York, 2003.
00. Central Events (Keynotes, EERA-Panel, EERJ Round Table, Invited Sessions)
Network 1. Continuing Professional Development: Learning for Individuals, Leaders, and Organisations
Network 2. Vocational Education and Training (VETNET)
Network 3. Curriculum Innovation
Network 4. Inclusive Education
Network 5. Children and Youth at Risk and Urban Education
Network 6. Open Learning: Media, Environments and Cultures
Network 7. Social Justice and Intercultural Education
Network 8. Research on Health Education
Network 9. Assessment, Evaluation, Testing and Measurement
Network 10. Teacher Education Research
Network 11. Educational Effectiveness and Quality Assurance
Network 12. LISnet - Library and Information Science Network
Network 13. Philosophy of Education
Network 14. Communities, Families and Schooling in Educational Research
Network 15. Research Partnerships in Education
Network 16. ICT in Education and Training
Network 17. Histories of Education
Network 18. Research in Sport Pedagogy
Network 19. Ethnography
Network 20. Research in Innovative Intercultural Learning Environments
Network 22. Research in Higher Education
Network 23. Policy Studies and Politics of Education
Network 24. Mathematics Education Research
Network 25. Research on Children's Rights in Education
Network 26. Educational Leadership
Network 27. Didactics – Learning and Teaching
The programme is updated regularly (each day in the morning)
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.