Research-integrating teaching offers a collective approach to engage students and researchers in real research questions, introducing them to authentic problem-solving strategies. In experimental research-integrating teaching, various different data are acquired and often analyzed by using specialized software programs. However, learning to operate these programs can sometimes divert attention from the research itself. To keep the focus on the research, we have developed a Python-based dashboard (PYDA) and implemented it successfully in a research-integrating course on intrinsically disordered proteins. PYDA simplifies data analysis by handling experimental data from techniques such as liquid chromatography, far-ultraviolet circular dichroism, and fluorescence spectroscopy in a unified way. Developed in Python by using the Plotly Dash framework and hosted on Heroku, PYDA allows students to visualize, convert, and analyze data without extensive prior knowledge of Python. By providing a streamlined, flexible, and customizable solution, PYDA enables students to focus on research and hypothesis development, fostering digitally competent and inquiry-driven problem solvers. PYDA is supplied with a set of example files that allows the user to test the program. These files can be accessed as the last item in the dropdown menu.ABSTRACT
With the arrival of new technologies, the biological sciences have become significantly more quantitative over the past 30 years. These new approaches have drawn in researchers from a broad range of disciplines; for example, trained physicists are now commonplace among biology department faculty. Yet, education in the biological sciences often does not reflect this large shift. Here, we outline a new program developed and taught at the University of Warwick to tackle the challenge of bringing quantitative, interdisciplinary education to the biosciences. We provide an overview of the course and the rationale for its structure. We then discuss lessons learned to aid others planning to implement interdisciplinary undergraduate courses based on teaching from research.ABSTRACT