Coming Back Home Safely is a safety game that sensitises workers throughout the company to key safety requirements, with the ultimate aim to significantly reduce the number of serious accidents. The game follows a simple but clever concept that refreshes topical knowledge of practices and procedures. More sophisticated concepts such as ‘shared vigilance’ are addressed as well. Feedback has been integrated to help people reflect on their own safety-related behaviour.
The purpose of the course is to help support staff in private equity companies to develop a better understanding of the industry.
The course was developed as a full day simulation exercise. Supported by EVCA staff, teams work through all the stages of a fund raising and investment process, competing to offer their investors an optimal return.
Care was taken to model the logic of venture capital and private equity investments as closely as possible. The result is a fun and intense learning experience in which participants build a better understanding of the drivers behind the industry.
The Umicore Way Game was developed to help employees worldwide internalise the company's code of conduct and its vision on sustainability and human rights policies.
It is a board game that can be played by teams with their supervisors. It is also very suitable to be integrated in a company introduction course for new employees.
At the heart of the learning game is a set of real-life dilemmas that provoke reflection and exchange between players against the background of the relevant policies.
Communicating Numerical Data is a 1,5-day course for scientists and senior scientists in pharmaceutical discovery and clinical research.
Effective visualisation of numerical data relies on the ability to think clearly and flexibly about data structures, on the awareness of the particular context in which the graph is produced and on the specific research question/message at hand.
This course offers a generic methodology to deal with a variety of scientific visualisation problems.
Participants generate their own dataset by means of a specially developed experimental toolkit. Based on these data, scientists are led to discover and apply the methodology.