The Rector’s Impulse Fund
Aim
The aim is to support innovative short-term projects that stimulate and improve teaching. In the 2023 funding period, the funds will flow entirely into the expansion of PBLabs, the promotion of interdisciplinary competencies at ETH through project-based and interdisciplinary teaching.
"Finding ideas for innovations is challenging. I am very pleased to support forward-looking impulses and visions through the Rector's Impulse Fund." Adrian Weiss
Digital methods in the teaching of architectural history. Prof. Dr. Maarten Delbeke, Dr. Olya Nikolaeva, D-ARCH. The JupyterNotebooks implemented with the funding were used in a first year course to familiarise students with tools for indexing architectural history contexts based on historical image and text sources.
FORESEE: Feedback for Embedded Systems Education Dr. Michele Magno, D-ITET The browser-based Integrated Development Environment (IDE) developed by the Center for Project-Based Learning supports students in deepening their skills in programming embedded systems. Code implementations and interactions with the hardware can be performed and tracked simultaneously physically and online. This enables timely feedback from the supervisors for large numbers of students, even outside of lab hours.
Computational Earth Sciences: Teaching at ETH and worldwide Prof. Dr. Andreas Fichtner, Dr. Gregory De Souza, D-ERDW. In the Earth and Climate Sciences BSc programme, the basics of programming and data science are continuously incorporated and deepened in 2-3 subject-specific subjects per semester. The funding was used to finance the development of specific JupyterNotebooks, which facilitate the low-threshold embedding of active teaching elements with a reference to data by a large number of lecturers in the degree programme and beyond ETH.
Expert lecturer network at D-USYS Dr. Barbara Templ, Dr. Anouk N'Guyen, D-USYS In this project, a community manager is analysing and strengthening the network of lecturers with teaching interests in data science and machine learning. She is also developing a tool that visualises student learning paths. Lecturers can thus estimate the expected prior knowledge and study programmes can include the information in curriculum planning.
A task library for the acquisition of computational competencies in Agricultural Sciences Prof. Dr. Nina Buchmann, Dr. Regine Maier, Dr. Iris Feigenwinter, D-USYS. The project initiates the development and expansion of research-related exercises and data sets in disciplinary courses in the bachelor programme. JupyterNotebooks and R are used to visualize data sets from the respective discipline, to form own hypotheses, and to question and further develop existing subject-specific understanding.
By the Rector's Impulse Fund
- Machine learning in the curriculum for Pharmaceutical Students (D-CHAB)
- Engineering Design Optimization using Machine Learning (EDO4ML) (D-MAVT)
- Application of machine learning in climate risk assessment and climate adaptation options appraisal (D-USYS)
- Food Systems Data Science: Interactive ML tutorials for food scientists (D-HEST)
- Quizzes in JupyterNotebooks for interactive group exercises (D-MAVT)
- Embedding Computational Competencies in Mathematics Education for LifeSciences (D-MATH, Service)
By innovedum in the context of the focus topics "Educational media for visualisation and simulation" and "Transferable competences":
- A Jupyter-based toolkit for teaching computational analysis and visualization to Food Science students
- Integrating JupyterNotebooks into the classroom to improve computational competence
- Interactive educational media for Food Biotechnology via Jupyter
- Interactive open-code computer simulation exercises promote a deeper understanding of quantitative phenomena in bioanalytics
- Interactive animations on numerical methods
- JupyterNotebooks in laboratory teaching for environmental engineers
- Interactive online learning for Control System 2
- Making dynamics more dynamic: interactive learning elements in a large engineering bachelor lecture