Introduction

Problem-solving is a key component to be successful in a modern society. With the use of PISA data, it is possible to identify the predictors of the problem-solving competence. In this study, these factors were identified using PISA 2012 data from six countries (two high, two medium, and two low achieving countries as a result of problem-solving assessment). Additionally, detailed analyses were conducted to understand what would be the problem-solving performance differences among these countries if they had similar mathematics performance on PISA.     

In today’s modern society and workplaces, necessity to solve non-routine or creative problems encountered almost every day increases. Instead of students who could only perform routine and algorithmic task by repeating commands of instructors, students who could overcome complex, non-routine tasks persistently are goals of educational systems to prepare them for tomorrow’s world. With providing separate problem-solving domain, PISA aimed to measure how well 15-year-olds were educated to cope with real life problem situations they have never met before. The creative problem-solving assessment of PISA gives emphasis to cognitive processes activated when solving problems, rather than solving problems related to specific school subjects. Items in problem-solving do not require any content expertise as much as possible (OECD, 2014). Subject specific problem-solving tasks are also measured in other sections of PISA assessment, such as in mathematics domain (OECD, 2013). PISA reported related validity analyses which showed that problem-solving constituted a separate domain from mathematics and other domains (OECD, 2014). 

                It is important to note that, some countries performed better or worse than expected on problem-solving compared to their mathematics performance. For example, among high, medium and low achieving countries, Korea, Norway, and Serbia got higher scores than expected on problem-solving, respectively. However, among high, medium and low achieving countries, the Netherlands, Ireland, and Turkey got lower scores than expected on problem-solving, respectively (OECD, 2014). Therefore, identifying predictors of problem-solving performance is expected to give clues about incentives behind these performance differences. Investigating correlates of creative problem-solving measured in PISA 2012 is a novel topic which is expected to contribute to the educational literature.                                 

The problem-solving performance differences within a country and between countries could be related to student-level and school-level factors. Student-level variables that could be predictors of problem-solving performances in PISA are economic, social and cultural status, perseverance and openness for problem solving, experience with pure and applied mathematics tasks at school. School-level variables that could be predictors of problem-solving performance in PISA are class size, proportion of certified teachers, proportion of teachers with ISCED 5A, quality of school educational resources, extracurricular creative activities at school, mathematics extracurricular activities at school.

It is expected from schools not only to develop regular curriculum based objectives but also to develop students’ problem-solving skills. Students should be equipped with better problem solving skills. In order to achieve this, educators should be informed about student and school characteristics that are effective in predicting problem-solving skills. Investigating significant predictors of problem-solving on high, medium and low achieving countries is expected to give some clues. OECD reported that some countries performed lower than expected on problem solving compared to their mathematics scores (OECD, 2014). Therefore, what would be the expected problem-solving performance of these countries was also necessary to investigate. This study contributes to the literature by identifying correlates of problem-solving performance on variety of countries. The research questions of this study are:

1. How do student and school level factors predict students’ problem-solving performances in high, medium and low achieving countries in PISA 2012?  
2. What would be the problem-solving performance differences among these countries, if students had similar mathematics performance?

Muthén, L.K., & Muthén, B.O. (2015). Mplus User’s Guide. Seventh Edition. Los Angeles, CA: Muthén & Muthén OECD (2013). PISA 2012 Assessment and Analytical Framework: Mathematics, Reading, Science, Problem Solving and Financial Literacy. Paris, France: OECD Publishing. http://dx.doi.org/10.1787/9789264190511-en OECD (2014). PISA 2012 Results: Creative Problem Solving: Students’ Skills in Tackling Real-Life Problems (Volume V). Paris, France: OECD Publishing. http://dx.doi.org/10.1787/9789264208070-en