Abstract
Previous studies have documented that students have difficulties in mathematical modeling competency. The current research is an attempt to investigate the issue of student’s mathematical modeling competency in pre-service mathematics teacher in Indonesia and its analysis in term of Cumulative Grade Points Average (CGPA) gap in Riau Province, Indonesia. The research involved a total of 100 pre-service teacher students in Universitas Islam Riau (UIR). A survey design was employed to investigate the students’ mathematical modeling competency using questionnaire of mathematical modeling test. The quantitative data were statistically analyzed using the SPSS 22.0. The descriptive analysis included the percentage, mean and standard deviation while inferential analysis involved Pearson correlation analysis. The results indicated that pre-service mathematics teacher education in Indonesia had moderate level of mathematical modeling competency. However, using graphical representation and interpreting and relating the mathematical solution to the real world context are the most two difficulties in mathematical modeling. At the same time, there was not a significant relationship between CGPA and mathematical modeling competency.
Highlights
Trend of increased reliance on digital technology influences education and training necessities
The results indicated that pre-service mathematics teacher education in Indonesia had moderate level of mathematical modeling competency
In the current research, comparing the sub-competencies of mathematical modeling competency in pre-service mathematics teacher in Indonesia, the results indicated that pre-service mathematics teacher education in Indonesia had moderate level of mathematical modeling competency
Summary
Trend of increased reliance on digital technology influences education and training necessities. How to persuade students in authentic problem solving. Since traditional forms of problem solving are seen as independent of the development of core mathematical concepts, understandings, and processes in which students do not have opportunity to investigate complex, messy and real-world data (English, Lesh, & Fennewald, 2008), application and modelling in mathematics classroom obtain strong support from several educational researcher during the last few decades (Niss, Blum, & Galbraith, 2007; Yuanita & Zakaria, 2016) especially using technology (Maat & Zakaria, 2011)
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