@inproceedings{Fuhrmann, author = {Fuhrmann, Thomas}, title = {Let the students publish}, series = {IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE), 26-29 August 2013, Bali Dynasty Resort, Kuta, Indonesia}, booktitle = {IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE), 26-29 August 2013, Bali Dynasty Resort, Kuta, Indonesia}, publisher = {IEEE}, isbn = {978-1-4673-6355-6}, doi = {10.1109/TALE.2013.6654515}, abstract = {In technical study programs on the bachelor level the focus is mainly directed on the scientific education in theory and practice. Publication is usually started during the PhD phase when students write their first scientific papers. During the last years some very successful projects were made at the university of applied sciences Regensburg to motivate bachelor students doing their first own small publications. The results of these projects are presented in this paper and ideas how students can publish are given.}, language = {en} } @inproceedings{Fuhrmann, author = {Fuhrmann, Thomas}, title = {Course Preparation Time Optimization System for Improved Didactic Outcome}, series = {2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET), 07-09 November 2022, Antalya, Turkey}, booktitle = {2022 20th International Conference on Information Technology Based Higher Education and Training (ITHET), 07-09 November 2022, Antalya, Turkey}, publisher = {IEEE}, isbn = {978-1-6654-8908-9}, doi = {10.1109/ITHET56107.2022.10031642}, abstract = {Due to the various demands for lecturers, there is only a limited time to prepare lectures and lab courses. Therefore, it is necessary to invest the time target-oriented for optimal student learning success. A theoretic model is developed to structure course preparation work regarding scientific content, didactic preparation, and course presentation. Model parameters have to be chosen for each course depending on topic complexity, the lecturer's prior knowledge, and the already available preparation from the prior semesters. With these parameters, a course preparation model for a complete semester is developed. Analytic models for different optimization strategies are introduced according to the overall goal of the lecturer. Numerical optimization is done to find the appropriate course preparation times to reach an optimal course preparation for high student learning success. It is seen that due to the different optimization strategies, the preparation time results vary and no single truth is given. But this optimization system gives hints on how to invest preparation time target-oriented for high student learning success.}, language = {en} } @inproceedings{FuhrmannNiemetz, author = {Fuhrmann, Thomas and Niemetz, Michael}, title = {Analysis and Improvement of Engineering Exams Toward Competence Orientation by Using an AI Chatbot}, series = {Towards a Hybrid, Flexible and Socially Engaged Higher Education: Proceedings of the 26th International Conference on Interactive Collaborative Learning (ICL2023), Volume 1}, booktitle = {Towards a Hybrid, Flexible and Socially Engaged Higher Education: Proceedings of the 26th International Conference on Interactive Collaborative Learning (ICL2023), Volume 1}, publisher = {Springer Nature}, address = {Cham}, isbn = {9783031519789}, issn = {2367-3370}, doi = {10.1007/978-3-031-51979-6_42}, pages = {403 -- 411}, abstract = {ChatGPT is currently one of the most advanced general chatbots. This development leads to diverse challenges in higher education, like new forms of teaching and learning, additional exam methods, new possibilities for plagiarism, and many more topics. On the other side with the development of advanced AI tools, pure knowledge will be less and less important, and demands from industry will change toward graduates with higher competencies. Education has therefore to be changed from knowledge-centered toward competence centered. The goal of this article is to use ChatGPT for analyzing and improving the competence orientation of exams in engineering education. The authors use ChatGPT to analyze exams from different engineering subjects to evaluate the performance of this chatbot and draw conclusions about the competence orientation of the tested exams. The obtained information is used to develop ideas for increasing the competence orientation of exams. From this analysis, it is visible that ChatGPT gives good performance mainly where knowledge is tested. It has, however, much more problems with transfer questions or tasks where students need creativity or complex insights for finding new solutions. Based on this result, exams and also lectures can be optimized toward competence orientation.}, language = {en} }