[논문]Investigating Students' Profiles of Mathematical Modeling: A Latent Profile Analysis in PISA 2012

SeoJin Jeong; Jihyun Hwang; Jeong Su Ahn

doi:10.7468/jksmed.2023.26.3.235

[국내논문] Investigating Students' Profiles of Mathematical Modeling: A Latent Profile Analysis in PISA 2012 원문보기

Journal of the Korean Society of Mathematical Education. Series D: Research in mathematical education, v.26 no.3, 2023년, pp.235 - 252

SeoJin Jeong (Department of Mathematics Gifted Education, Korea National University of Education) , Jihyun Hwang (Department of Mathematics Education, Korea National University of Education) , Jeong Su Ahn (Department of Mathematics Education, Korea National University of Education)

Abstract ▼ AI-Helper

We investigated the classification of learner groups for students' mathematical modeling competency and analyzed the characteristics in each profile group for each country and variable using PISA 2012 data from six countries. With a perspective on measuring sub-competency, we applied the latent profile analysis method to student achievement for mathematical modeling variables - Formulate, Employ, Interpret. The findings showed the presence of 4-6 profile groups, with the variables exhibiting high and low achievement within each profile group varying by country, and a hierarchical structure was observed in the profile group distribution in all countries, interestingly, the Formulate variable showed the largest difference between high-achieving and low-achieving profile groups. These results have significant implications. Comparison by country, variable, and profile group can provide valuable insights into understanding the various characteristics of students' mathematical modeling competency. The Formulate variable could serve as the most suitable predictor of a student's profile group and the score range of other variables. We suggest further studies to gain more detailed insights into mathematical modeling competency with different cultural contexts.

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표/그림 (8)

그림 Figure 1. Mathematical modeling cycle in PISA 2012 (OECD, 2013, p. 26)
표 Table 1. Activities included in mathematical modeling variable items (OECD, 2013, pp. 28-31)
표 Table 2. Data description
표 Table 3. Descriptive statistics of mathematical modeling variables
표 Table 4. Indicators of profile model fit by country
표 Table 5. Distribution of students of each country's profile group and the average student achievement for each variable
그림 Figure 2. Distribution of profiles in each country for each mathematical modeling variable
그림 Figure 3. Distribution of countries in each profile for each mathematical modeling variable

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