Factors Predicting Collaborative Problem Solving: Based on the Data From PISA 2015

Abstract

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Collaborative problem solving (CPS) competency is critical in the twenty-first century. The Program for International Student Assessment (PISA) launched a large-scale assessment of CPS competency for the first time in 2015. Beijing, Shanghai, Jiangsu, and Guangdong provinces in China participated the assessment and scored an average of 496, which was slightly lower than the OECD average 500 and ranked 25th among the 51 countries and economies participating in the assessment. Therefore, this research was conducted to dig into the factors predicting students’ CPS competency, and help students improve it. Most research about CPS has fallen into the construction of the CPS framework and the effectiveness of CPS; research focusing on the factors predicting CPS competency is rare. Accordingly, a hierarchical linear model (HLM) was constructed to investigate the factors predicting students’ CPS competency in the current research. The model revealed that there was a large difference of students’ CPS competency among schools. In addition, among student-level variables, gender, grade, ESCS, ICT resources, students’ attitude toward CPS, and teacher unfairness were effective in predicting students’ CPS competency; among school-level variables, school location, schools’ ESCS and the proportion of all teachers fully certified predicted students’ CPS competency positively. The findings implied that in order to enhance students’ CPS competency, CPS competency training should be permeated through all the subjects; schools should employ teachers who are fully qualified; teachers should treat each student fairly; and students should be provided with more ICT resources and etc.

Keywords

• PISA 2015
• hierarchical linear model
• ESCS
• factors predicting CPS
• collaborative problem solving