@inproceedings{DoehringStieglitzHudecetal.2022, author = {D{\"o}hring, Thorsten and Stieglitz, Veronika and Hudec, Rene and Sapsai, Iryna and Friedrich, Peter and Burwitz, Vadim}, title = {Characterization of a lobster-eye type X-ray telescope}, series = {EOSAM-Conference}, volume = {2022}, booktitle = {EOSAM-Conference}, organization = {TH Aschaffenburg}, pages = {1 -- 1}, year = {2022}, abstract = {Lobster-eye type X-ray telescopes use reflecting plano mirrors under grazing incidence and can observe a large field of view. As part of a Bavarian-Czech cooperation, two telescopes were build, equipped with mirrors coated with gold and iridium. Their X-ray characterization was carried out at the PANTER test facility, which simulates parallel starlight incident on the telescopes. The telescopes have an angular resolution of about 4 arc minutes in X-rays and a focal length of about 2 meters. The used X-ray mirrors reflect and focus visible light as well; their functionality in the optical regime was checked in laboratory tests. Now another test campaign will be carried out to examine the telescope resolution for real objects of the visible night sky and the imaging properties for star constellations.}, subject = {R{\"o}ntgenteleskop}, language = {en} } @inproceedings{ValenciaNormannSapsaietal.2023, author = {Valencia, Yeimy and Normann, Marc and Sapsai, Iryna and Abke, J{\"o}rg and Madsen, Anders L. and Weidl, Galia}, title = {Learning Style Classification by Using Bayesian Networks Based on the Index of Learning Style}, series = {ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education, June 2023}, booktitle = {ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education, June 2023}, doi = {10.1145/3593663.3593685}, pages = {73 -- 82}, year = {2023}, subject = {Lernstil}, language = {en} } @article{SapsaiValenciaAbke2023, author = {Sapsai, Iryna and Valencia, Yeimy and Abke, J{\"o}rg}, title = {Learning Analytics Dashboard for Educators: Proposed Project to Design with Pedagogical Background}, series = {ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education}, volume = {2023}, journal = {ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education}, number = {ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education}, doi = {https://doi.org/10.1145/3593663.3593686}, pages = {38 -- 47}, year = {2023}, abstract = {In this article, the authors describe a prototype of a Learning Analytics Dashboard (LAD) for educators. It is based on the analysis of pedagogical actions and taking into the process and learning style of students in an online environment based on learning analytics (LA). A description of the Dashboard structure, divided into levels and categories based on available learning analytics, will allow the educator to dive deeper into the online course themselves and explore more. It will also allow them to determine the level of student performance, identify gaps in learning materials, and research student data. The authors have identified further directions for the development of a LAD for a professor, including modeling algorithms for researching student behavior and learning style using Artificial Intelligence and presenting LA in a visualized form. This paper shows the stages of creating a professor's LAD prototype as a functional part of the adaptive learning system in the HASKI-System to analyze visual information obtained from LA and the possibilities to monitor the learning process, learning progress, student activity, and make decisions on careful intervention in the students' learning process.}, subject = {Lerntechnik}, language = {en} }