A Modular Approach to Teaching Mathematical Modeling in Biotechnology in the Undergraduate Curriculum

Autor/inn/en	Larripa, Kamila R.; Mazzag, Borbala
Titel	A Modular Approach to Teaching Mathematical Modeling in Biotechnology in the Undergraduate Curriculum
Quelle	In: PRIMUS, 26 (2016) 5, S.485-504 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1051-1970
DOI	10.1080/10511970.2015.1104524
Schlagwörter	Mathematical Models; Biotechnology; Undergraduate Students; College Science; Majors (Students); Mathematics Instruction; Science Instruction; Computation; Interdisciplinary Approach; Course Organization; Units of Study; California + Suchen Sie Ihr Suchwort? Mathematical model; Mathematisches Modell; Biotechnologie; Mathematics lessons; Mathematikunterricht; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Fächerübergreifender Unterricht; Fächerverbindender Unterricht; Interdisziplinarität; Course organisation; Kurskonzept; Lerneinheit; Kalifornien
Abstract	Our paper describes a solution we found to a still existing need to develop mathematical modeling courses for undergraduate biology majors. Some challenges of such courses are: (i) relatively limited exposure of biology students to higher-level mathematical and computational concepts; (ii) availability of texts that can give a flavor of how contemporary biological problems are approached with quantitative methods; (iii) expectations to cover specific mathematical (or biological) content rather than teach a problem-solving approach. We solved these challenges by designing a course where several modules were developed, each beginning with a presentation from a campus expert in a biological area of research and concluding with a seminar-style student-led paper presentation of an article that addresses the biological problem using mathematical and computational tools. The aim of the course was to expose students to the vast possibilities and potential in quantitative biology, and to give them a vocabulary to collaborate with mathematicians, statisticians, and computer scientists. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01