Using External Representations to Support Mathematical Modelling Competence in Biology Education

Author:

Stöger Benjamin,Nerdel Claudia

Abstract

AbstractThe best explanatory approaches in the natural sciences are based on mathematical models. The COVID-19 pandemic or climate change illustrate the importance of mathematical modelling. This study focusses on the influence of external representations, texts, diagrams, and images, as well as mathematical expertise, on modelling competence for biochemical concepts. Especially the cross-curricular aspect of these tasks shows the influence of different science disciplines on concrete skills and abilities in biology. Consequently, the participants were asked to complete an enzyme kinetics task that was based on Schmidt and Di Fuccia’s (Giornale Di Didattica E Cultura Della Società Chimica Italiana 34(3):331–335, 2012) seven-step modelling cycle. A mixed-methods approach, involving quantitative frequency analysis and a qualitative analysis of the participants’ statements, was used. Elaboration behaviour was found to be increased through representation, as well as expertise. These results indicate the positive influence of external representations and mathematical competence on modelling competence. Furthermore, different biological topics (e.g. epidemiology) need to be elaborated as well.

Publisher

Springer International Publishing

Reference39 articles.

1. Ainsworth, S. (1999). The functions of multiple representations. Computers & Education, 33(2–3), 131–152.

2. Blum, W., & Borromeo Ferri, R. K. (2009). Mathematical modelling: Can it be taught and learnt? Journal of Mathematical Modelling and Application, 1(1), 45–58.

3. Blum, W., & Leiss, D. (2005). Modellieren im Unterricht mit der ‘Tanken’-Aufgabe. Mathematik Lehren, 128, 18–21.

4. Blum, W., & Leiss, D. (2007). Investigating quality mathematics teaching: The DISUM project. Developing and researching quality in mathematics teaching and learning. Proceedings of MADIF, 5, 3–16.

5. Borromeo Ferri, R. (2006). Theoretical and empirical differentiations of phases in the modelling process. ZDM – Mathematics Education, 38(2), 86–95.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3