Determining the Relationships between Selected Variables and Latent Classes in Students’ PISA Achievement

Seher Yalcin

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Abstract


The purpose of this study was to identify the multilevel latent classes for reading, mathematics, and science success of the students, who participated in the Programme for International Student Assessment (PISA) 2012 from Turkey and to determine the predictive ability of i) students‟ perseverance, ii) their openness to problem solving, iii) their economic, social, and cultural status (ESCS), and iv) resources of school in relation to the determined student and school classes using a multilevel approach. The population of this research was school principals and all the 15-year-old students, who attended PISA 2012 in Turkey. Analyses were conducted with the data obtained from a total of 3,196 students and 169 school principals. In the first step, a multilevel latent class analysis was used to investigate the number of these classes in schools reading, mathematics, and science success of the students. Then, a three-step analysis was undertaken to determine the predictive ability of the chosen variables for the identified classes. The results indicated that all the chosen variables significantly predicted the school-level latent class membership. Moreover, analyses suggested that the students‟ ESCS was the most important factor affecting their achievement.

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References


Yalcin, S. (2017). Determining the relationships between selected variables and latent classes in students‟ PISA achievement. International Journal of Research in Education and Science (IJRES), 3(2), 589-603. DOI: 10.21890/ijres.328089


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