SCIRP Mobile Website
Paper Submission

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.


Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
Paper Publishing WeChat
Book Publishing WeChat

Article citations


Houston, K. (2007). Assessing the “Phases” of Mathematical Modelling. In W. Blum, H.-W. Henn, P. L. Galbraith, & M. Niss (Eds.), Modelling and Applications in Mathematics Education: The 14th ICMI Study (Vol. 10, pp. 249-255). New York: Springer.

has been cited by the following article:

  • TITLE: Mathematical Modelling Competency for Indonesian Students in Mathematics Education Programmes

    AUTHORS: Riyan Hidayat, Zanaton H. Iksan

    KEYWORDS: Mathematical Modeling Competency, Pre-Service Mathematics Teacher, CGPA

    JOURNAL NAME: Creative Education, Vol.9 No.15, November 16, 2018

    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 studentsin 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.