05 SES 10, Children and Youth at Risk and Urban Education
There are several crucial aspects that affect students and upgrade their status as ‘at risk’ in their educational experiences and lives. These aspects are bad family structures, school resources, low socio-economic status (SES) and etc. Among these, especially low SES of students was shown to have a negative relationship with achievement of students (Kalender & Berberoglu, 2009; Yayan & Berberoglu, 2004).
Students under influence of such factors are called disadvantaged. Some of these disadvantaged students tend to have several mechanisms to lessen the effects of above aspects. The individual coping-mechanisms, or protective factors, that students have or develop are mostly intelligence, temperament, internal locus of control, and autonomy (Beauvais & Oetting, 1999; Greene & Conrad, 2002). Although it is really difficult to change the conditions that put the students at risk, it is crucial that the disadvantaged students learn to deal with their problems and improve their academic skills (Alva, 1991); thus, they can provide themselves with a good learning opportunity, which makes them academically resilient (Martin, 2002). Hanson and Austin (2003) reported that the students who have higher resiliency have higher achievement levels in schools. Also there are reported findings that academic resilience does not only improve students’ achievement at school, but also it provides several positive outcomes in their life like stronger social relations, less emotional and behavioural problems and alike.
Among the protective factors which can be taught at schools is problem-solving skill, which is related to ability of abstract and flexible thinking, finding out alternative solutions (Benard, 1993; Rutter & Quinton, 1994). Teaching problem-solving skills is an integral part of all nations’ curricula. Although problem-solving is taught as embedded into science and mathematics courses (National Council of Teachers of Mathematics, 1989; National Research Council, 1989; Turkish Ministry of National Education, 2008), the primary purpose is to make students gain skills they will need to use when solving problems in daily life (Krulik & Rudnick, 1989).
One of the most comprehensive data sets comes from Programme for International Student Assessment (PISA) conducted by Organisation for Economic Co-operation and Development (OECD). Approximately 6% of students across its member countries are defined as resilient by OECD. Preliminary results on PISA 2012 show that, disadvantaged students in countries where SES is lower received lower scores not only in mathematics but also in some other dimensions such as engagement, drive, and motivation. On the other hand, resilient students can get higher scores both in mathematics and other dimensions. Accordingly, OECD suggests that putting efforts to increase disadvantaged students’ performance through additional instruction be a key priority for policy makers of the low SES countries (2013).
Although the primary focus of PISA 2012 is mathematics, problem-solving is one of the minor areas. Preliminary results indicated that students who rated themselves as open to problem solving have higher scores in literacy domain (OECD, 2013).
Turkey was among the top 8 countries that had the highest resilient student ratios (OECD, 2013). Therefore, it can be said that Turkey constitutes a good example to study resilient students. In a study on PISA 2009, it was shown that while resilient ones generally went up to 3rd proficiency level, most of the disadvantaged students reached only 2nd level (Findik & Kavak, 2013).
In the light of importance of problem solving and differences between resilient and disadvantaged students, investigation of determinant related to problem solving is of importance in finding out variables increasing student performance. Studies in the literature generally focused on differences between resilient and non-resilient groups. However, the present study focuses on the differences between low-achievers and resilient students.
Alva, S.A. (1991). Academic invulnerability among Mexican-American students: The importance of protective resources and appraisals. Hispanic Journal of Behavioural Sciences, 13(1), 18-34 Beauvais, F. & Oetting, E.R. (1999). Durg use, resilience, and the myth of the golden child. In Glantz, M.D. Johnson, J.L. (Eds.), Resilience and development: Positive life adaptations (pp. 101-107). New York: Kluwer Academic/Plenum Publishers. Benard, B. (1993). Fostering resiliency in kids. Educational Leadership, 51(3), 44-48 Fındık, L. Y., & Kavak, Y. (2013). Assessing the PISA 2009 Achievement of Disadvantaged Students in Turkey. Kuram ve Uygulamada Eğitim Yönetimi. Educational Administration: Theory and Practice, 19(2), 249-273. Greene, R. & Conrad, A.P. (2002). Basic assumptions and terms. In R. Greene (Ed.), Resiliency: An integral approach to practice policy, and research (pp. 29-62). Washington, DC: NASW Press. Hanson, T. L. & Austin, G.A. (2003). Are student health risks and low resilience assets an impediment to the academic progress of schools? California Healthy Kids Survey Factsheet 3. Los Alamitos, CA: WestEd. Kalender, I. & Berberoglu, G. (2009). An assessment of factors related to science achievement of Turkish students. International Journal of Science Education, 31(10), 1379-1394. Krulik, S. & Rudnick, J. A. (1989). Problem Solving: A Handbook for Senior High School Teachers. Boston, MA: Allyn and Bacon. Martin, A. (2002). Motivation and Academic Resilience: Developing a Model for Student Enhancement. Australian Journal of Education, 46(1), 34-49. National Council of Teachers of Mathematics (1989). Curriculum and evaluation standards for school mathematics. Reston, VA: Author. National Research Council (1989). Everybody counts. Washington DC: National Academy Press. OECD (2013), PISA 2012 Results: Excellence Through Equity: Giving Every Student the Chance to Succeed (Volume II), PISA, OECD Publishing. Rutter, M. & Quinton, D. (1994). Long-term follow-up of women institutionalized in childhood: Factors promoting good functioning in adult life. British Journal of Developmental Psychology, 18, 225-234. Sonquist, J.A., & Morgan, J. N. (1964). The detection of interaction effects: a report on a computer program for the selection of optimal combinations of explanatory variables. Monograph no: 35, Survey Research Center, Institute for Social Research, University of Michigan. Turkish Ministry of National Education [MNE] (2008) İlköğretim matematik dersi öğretim programı (6-8. sınıflar) (Elementary school mathematics curriculum (grades 6-8)). Ankara, Turkey: MNE. Yayan, B. & Berberoğlu, G. (2004). A Re-Analysis of the TIMSS 1999 Mathematics Assessment Data of the Turkish Students. Studies in Educational Evaluation. 30, 87-104.
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Network 1. Continuing Professional Development: Learning for Individuals, Leaders, and Organisations
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