No abstract

No abstract

This concept paper presents the large-scale measures and results that the Faculty of Engineering of the Friedrich-Alexander Universität Erlangen-Nürnberg (FAU) has developed to shape the future of learning and teaching of propaedeutic skills in the field of mathematics as a central basis of engineering subjects and to inspire pupils and young people for engineering studies. Since 2020, the Faculty of Engineering has developed a three-tier, structured voluntary program that is attended by several thousand pupils and freshmen per year: 1. Summer review courses in mathematics for pupils after the 10th and 11th school year during the summer holidays in accordance with the Bavarian school curriculum 2. School leaving exam preparation courses in mathematics shortly before the university-entrance diploma acquired at a secondary school in Germany, the socalled "Abitur" 3. Math review courses for freshmen. The methodological approach of the article lies in the presentation of the educational measures and in the analysis of the results of systematic student evaluations. This leads to generalizable, transferable recommendations for the future design of such large-scale measures for universities, derived from answering the proposed research questions and evaluation results

No abstract

Abstract. When modeling technical processes, the training data regularly come from test plans, to reduce the number of experiments and to save time and costs. On the other hand, this leads to unobserved combinations of the input variables. In this article it is shown, that these unobserved configurations might lead to un-trainable parameters. Afterwards a possible design criterion is introduced, which avoids this drawback. Our approach is tested to model a welding process. The results show, that hybrid Bayesian networks are able to deal with yet unobserved inand output data.