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

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.

PhysiCell Studio: a graphical tool to make agent-based modeling more accessible

“…By combining graduate and undergraduate students in regular lab meetings, we foster both education and research. Undergraduates learn more about active research projects (like the Studio and models developed using it); graduate students, postdocs, and staff become mentors [ 17 ] . …”

Digital Literacy 5.0 to Enhance Multicultural Education

“…It prepares a new generation of scientists proficient in both biological and computational sciences, fostering innovation in biomedical research. Additionally, it facilitates interdisciplinary collaborations, contributing to advancements in personalized medicine, drug discovery, and our comprehension of complex biological systems (262).…”

PhysiCell training apps: A case study for creating interactive training materials for scientific software packages

“…They identified that most such students seek to use computational modeling to answer domain-specific research questions that cannot be answered in wet labs. It shows that many scientists with the minimum computational background are potential users of computational modeling and simulation tools.Madamanchi et al [6] discussed the need for user-friendly tools in computational modeling training, along with the potential of using focused web applications ("microapps") for education and training. In this report, we demonstrate a suite of microapps to address the training needs of new multidisciplinary users of biological simulation software.…”