Problem Solving Skills-Related Determinants Associated with Performance of Resilient Students in PISA 2012

Author(s):

Ilker Kalender(submitting)Ayse Aydiner(presenting)

Conference:

ECER 2014

Network:

05. Children and Youth at Risk and Urban Education

Format:

Paper

Session Information

05 SES 10, Children and Youth at Risk and Urban Education

Paper Session

Time:

2014-09-04

15:30-17:00

Room:

B017 Anfiteatro

Chair:

Mark Hadfield

Contribution

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 3^rd proficiency level, most of the disadvantaged students reached only 2^nd 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.

Method

Resilient students are defined, in PISA, as those who are in the bottom quarter of index of economic, social and cultural status (ESCS) in respective country and scores in the top quarter across students from all countries after accounting for socio-economic background (OECD, 2013). ESCS is a variable computed using student reports on parental occupation, the highest level of parental education, and an index of home possessions related to family wealth, home educational resources and possessions related to “classical” culture in the family home. Two dimensions assessed by PISA 2012 related to problem solving are perseverance (5 items) and openness for problem solving (5 items). Although separate latent variables for both aspects using respective items were defined, moderate correlations among the items led the researchers to investigate problem solving dimension at item level, rather than using latent variables. A total number of 4848 Turkish students were included in PISA 2012 cycle. First disadvantaged students who are at the bottom quarter based on ECSC index of Turkey were selected (n = 1232). Among them, those who performed below 33rd percentile and above 67th percentile in reading subdomain across all countries were labelled as low-achievers (n = 562) and resilient (n = 223), respectively. Mean reading scores were 376 (proficiency level-4) and 553 (proficiency level-2), for low-achievers and resilient students, respectively. To determine the items related to openness for problem solving and perseverance maximizing difference in achievement scores with respect to resilient and low-achievers, Chi-squared Automatic Interaction Detector (CHAID) analysis, a segmentation method, was employed (Sonquist and Morgan 1964). This method was used to determine the predictor variables which maximized the differentiation on a target variable. CHAID created clusters first selecting the strongest predictor created the highest differentiation on target variables. Then by selecting the second predictor associated with target variables, additional clusters were created and this produce was repeated until no significant differentiation was left. Two CHAID analyses were conducted on low-achievers and resilient students, both disadvantaged, to find out the variables related to two indicators, openness for problem solving and perseverance on reading achievement.

Expected Outcomes

For openness for problem solving, the single variable which created a differentiation between reading achievement levels of resilient students seemed the statement “I can easily link facts together”. Student who rated themselves on this item with a score below 3 significantly performed better in reading, although they were still at proficiency level 3. For perseverance, students, who indicated that they postponed difficult problems by giving a score of 1 when confronted a problem, significantly underperformed and were placed at proficiency level of 3. Students who gave scores of 2 or above for this item showed significantly higher performance. Follow-up analyses were conducted on low-learners using the items defined by CHAID procedure as significant predictors of reading scores. For the item “I can easily link facts together” under the openness for problem solving trait; for those who gave for the item among low-achievers, there was no significant difference in mean reading scores with respect to response categories. In other words, the item did not discriminate low-achievers in reading scores. Similarly, the responses given for the item “I put off difficult problems” from the perseverance trait seems to create a difference in reading performance. Results indicated that two indicators for problem solving skills, “I can easily link facts together” and “I put off difficult problems”, had a stronger relationship than other indicators with reading performance of students. Increasing students’ ability of linking facts in classes by teaching them how to do that and of coping postponement behaviours when confronted with difficult problems may provide significant performance increase for low-achievers. Analyses will be repeated on mathematics and science domains to further investigate the resiliency and literacy of students.

References

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.

Author Information

Ilker Kalender (submitting)

Bilkent University, Turkey

Ayse Aydiner (presenting)

bilkent university

curriculum and instruction

ankara

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