Chemistry fund promotes data-oriented chemistry education: RPTU receives around 100,000 euros
The Fonds der Chemischen Industrie (FCI) supports university teaching at 19 universities and 4 colleges across Germany so that students can prepare themselves in the best possible way for the working world in an increasingly digitalized chemical and pharmaceutical industry. The aim is to firmly anchor data science in chemistry studies. 100,000 euros from the funding pot will go to RPTU.
"With this funding, we want to enable students in all phases of chemistry studies to work on scientific questions in a data-based, critical and responsible manner - from digital data acquisition and algorithmic evaluation to the reflective interpretation of results. Individual elements such as electronic lab books are already part of our teaching. Now we are looking at the entire chain of creation and processing of scientific data," explains Georg Manolikakes, Professor at RPTU.
In future, chemistry students will receive basic knowledge in four coordinated areas from the first semester onwards, integrated into existing courses: an introduction to the Python programming language, modern research data management, working with large data sets and automated experiments.
With the help of the Python programming language, students will be able to write their own programs and use them to perform complex calculations, structure and evaluate large amounts of data automatically or control research equipment. In the area of research data management, the aim is to electronically document data from the laboratory practicals integrated into the degree course, to use it continuously during the successive practicals over the course of the semester and to analyze it at the end. Chemistry students also practise classifying and evaluating large data sets using their previously acquired knowledge.
In the Master's program, chemistry students learn how to use an automated synthesis platform. Such synthesis robots are already routinely used in industry to carry out a large number of experiments in the shortest possible time (high throughput experimentation). Different parameters or starting materials are systematically varied and empirically investigated simultaneously with the aim of determining optimum parameter values. By linking the experiments with Bayesian optimization, students gain insights into modern tools for experimental design.
All these measures are supplemented by accompanying didactic research, which examines the acquisition of skills and evaluates the effectiveness of the new teaching concepts. The project is based on established future skills and data literacy concepts and combines technical, reflective and ethical aspects of data work. The project is also closely linked to NFDI4Chem, a consortium in which scientific institutions across Germany work together to better collect, store and utilize data from chemistry. RPTU will make teaching materials and digital workflows openly accessible and integrate them into existing specialist community structures. The project thus strengthens future-oriented chemistry teaching and supports students in actively shaping the digital transformation of Chemistry 4.0.
The Chemistry department is also contributing 20% of its own funding to the teaching project. This own investment is a condition for the fund support and thus mobilizes further resources for improving the quality of university teaching.
Questions answered:
Prof. Dr. Georg Manolikakes
Department of Chemistry
at RPTU Kaiserslautern-Landau
E-mail: georg.manolikakes[@]chem.rptu.de