Developing Gamification Strategies for International, Interdisciplinary, Team-Based Online Courses in Engineering Design

Student motivation is a highly relevant topic, especially since the increased implementation of online courses during the Corona pandemic. The concept of gamification offers a modern approach to the strategic design of courses, among others, concerning the optimal motivation of participants. Based on a case study of the international, interdisciplinary online course of the International Design and Engineering Education Association (IDEEA) and the subsequent evaluation with modern digital simulation tools, this research shows how gamification strategies can be sustainably integrated into digital courses to strengthen the motivation and participation of students. The results show a fundamental consistency between the case study and the newly developed simulation model and will therefore be transferred into a process for the general application of gamification in courses for teaching staff at universities. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Improving Safety in Europe-Detecting Counterfeit Certificates from FFP2 Masks: A Text-Mining Approach

At the beginning of the Corona pandemic, there was a surge in demand for medical masks, especially FFP2 masks, which could not be adequately met by existing mask manufacturers. This led to new manufacturers of FFP2 masks entering the market. However, in order for these new suppliers to be allowed to offer these products in conformity with the law, the masks must be tested by an independent body (notified body). This testing usually takes several months and is associated with a number of bureaucratic hurdles and expenses. This led to the fact that untested masks were sold and are still being sold. In order to subsequently identify untested masks, we propose a method that automatically checks a specific document from the testing, namely the type examination certificate. To enable automated evaluation, this paper presents a text-mining approach for verification. It consists of three steps: i) requirements identification of certificates, ii) data extraction and analysis and iii) evaluation of the results using a decision tree classifier. Finally, the algorithm is validated using a case study of several counterfeit FFP2 type examination certificates. The result shows that the text-mining approach is capable of distinguishing fake from real certificates. The ability to analyze certificates in an automated way will completely change the way market surveillance authorities and accredited verification bodies check documents. © 2022 IEEE.