An In-Depth Analysis of the Issue of Sense of Belonging at School in the PISA 2003 Mathematical Literacy Study

By:

In 2003, Macao participated in the PISA mathematical literacy study. Macao’s 15-year-olds ranked ninth in the performance league table and in the same assessment sense of belonging at school was the lowest amongst 41 countries/economies. Similar low affective learning outcomes occurred in Hong Kong, Japan and Korea. Preliminary analyses revealed the following phenomenon: (1) students’ low sense of belonging at school is common in different types of schools, including in schools of different economic, social and cultural status of the home; (2) sense of belonging at school is not related to mathematical literacy; (3) students’ low sense of belonging is not related to number of times of grade repetition, grade studied at 15-year-old, and whether is Macao-born or an immigrant. In order to find out why there is a large proportion of students, of these some are high-performing, whose sense of belonging at school is below the OECD average, analysis of variances (ANOVA) are performed to locate factors that may have a bearing on the issue concerned. Three factors are discernible: (1) Attitude towards school; (2) Student-teacher relation; and (3) Teacher support. Based on these findings, Macao schools are informed to strengthen fostering of positive student attitudes toward school, establishing conducive and harmonious teacher-student relationships, and rendering academic support and day-care to students. In sum, schools are not only targeted at building minds but also hearts in the students.

Stream: Curriculum and Pedagogy; Student Learning, Learner Experiences, Learner Diversity

Paper: A paper has not yet been submitted.

Dr.Kwok-cheung Cheung is professor of curriculum and instruction at the Faculty of Education of the University of Macau. He is director of the Educational Testing and Assessment Research Centre, and national project manager of the Macao-China PISA studies. His research interests are on measurement and evaluation, as well as modeling of educational data.