Competencies in Mathematical Modelling Tasks: An Error Analysis
Hanti Kotze 1 *
More Detail
1 University of Johannesburg, Johannesburg, SOUTH AFRICA* Corresponding Author


This paper aimed to investigate the type of modelling task that may elicit competencies that are more aligned with demands from the biomedical technology industry. The inquiry identified strengths and weaknesses in students’ modelling competencies by analysing errors in two types of modelling tasks: atomistic and holistic. By using subtasks, errors could be identified according to the Newman error categories and compared with six modelling competencies according to the framework of Blum and Leiß. First-year biomedical technology students at a South African university made more errors in interpreting, validating and presenting, these being modelling competencies required to convert mathematical results to real-world results. The findings indicated that competencies embedded in atomistic tasks are more relevant to workplace demands in the local setting than those elicited in holistic modelling tasks. The implications for classroom practices are discussed.


This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, Volume 14, Issue 8, August 2018, Article No: em1567

Publication date: 02 Jun 2018

Article Views: 2443

Article Downloads: 1166

Open Access References How to cite this article