Supporting "Computational Apprenticeship" through Educational and Software Infrastructure: A Case Study in a Mathematical Oncology Research Lab

Autor/inn/en	Madamanchi, Aasakiran; Thomas, Madison; Magana, Alejandra; Heiland, Randy; Macklin, Paul
Titel	Supporting "Computational Apprenticeship" through Educational and Software Infrastructure: A Case Study in a Mathematical Oncology Research Lab
Quelle	In: PRIMUS, 32 (2022) 3, S.446-467 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Madamanchi, Aasakiran) ORCID (Magana, Alejandra) ORCID (Heiland, Randy) ORCID (Macklin, Paul)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1051-1970
DOI	10.1080/10511970.2021.1881849
Schlagwörter	Mathematics Instruction; Biological Sciences; Interdisciplinary Approach; Computation; Laboratories; Mentors; Undergraduate Students; Student Research; Apprenticeships; Mathematical Models; Computer Software; Educational Technology; Technology Uses in Education; Indiana + Suchen Sie Ihr Suchwort? Mathematics lessons; Mathematikunterricht; Abwasserbiologie; Fächerübergreifender Unterricht; Fächerverbindender Unterricht; Interdisziplinarität; Laboratory; Laboratorium; Studentenforschung; Apprenticeship; Lehre; Mathematical model; Mathematisches Modell; Unterrichtsmedien; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen
Abstract	There is growing awareness of the need for mathematics and computing to quantitatively understand the complex dynamics and feedbacks in the life sciences. Although several institutions and research groups are conducting pioneering multidisciplinary research, communication and education across fields remain a bottleneck. The opportunity is ripe for using education research-supported mechanisms of cross-disciplinary training at the intersection of mathematics, computation, and biology. This case study uses the computational apprenticeship theoretical framework to describe the efforts of a computational biology lab to rapidly prototype, test, and refine a mentorship infrastructure for undergraduate research experiences. We describe the challenges, benefits, and lessons learned, as well as the utility of the computational apprenticeship framework in supporting computational/math students learning and contributing to biology, and biologists in learning computational methods. We also explore implications for undergraduate classroom instruction and cross-disciplinary scientific communication. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01