TY - CHAP A1 - Weiss, Nils A1 - Renner, Sebastian A1 - Mottok, Jürgen A1 - Matoušek, Václav T1 - Automated Threat Evaluation of Automotive Diagnostic Protocols T2 - ESCAR USA, 2021, Virtual N2 - Diagnostic protocols in automotive systems can offer a huge attack surface with devastating impacts if vulnerabilities are present. This paper shows the application of active automata learning techniques for reverse engineering system state machines of automotive systems. The developed black-box testing strategy is based on diagnostic protocol communication. Through this approach, it is possible to automatically investigate a highly increased attack surface. Based on a new metric, introduced in this paper, we are able to rate the possible attack surface of an entire vehicle or a single Electronic Control Unit (ECU). A novel attack surface metric allows comparisons of different ECUs from different Original Equipment Manufacturers (OEMs), even between different diagnostic protocols. Additionally, we demonstrate the analysis capabilities of our graph-based model to evaluate an ECUs possible attack surface over a lifetime. KW - Automotive Diagnostic Protocols KW - Security Metrics KW - Automated Network Scan Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-29882 ER - TY - JOUR A1 - Maier, Robert A1 - Schlattl, Andreas A1 - Guess, Thomas A1 - Mottok, Jürgen T1 - CausalOps - Towards an industrial lifecycle for causal probabilistic graphical models JF - Information and Software Technology N2 - Context: Causal probabilistic graph-based models have gained widespread utility, enabling the modeling of cause-and-effect relationships across diverse domains. With their rising adoption in new areas, such as safety analysis of complex systems, software engineering, and machine learning, the need for an integrated lifecycle framework akin to DevOps and MLOps has emerged. Currently, such a reference for organizations interested in employing causal engineering is missing. This lack of guidance hinders the incorporation and maturation of causal methods in the context of real-life applications. Objective: This work contextualizes causal model usage across different stages and stakeholders and outlines a holistic view of creating and maintaining them within the process landscape of an organization. Method: A novel lifecycle framework for causal model development and application called CausalOps is proposed. By defining key entities, dependencies, and intermediate artifacts generated during causal engineering, a consistent vocabulary and workflow model to guide organizations in adopting causal methods are established. Results: Based on the early adoption of the discussed methodology to a real-life problem within the automotive domain, an experience report underlining the practicability and challenges of the proposed approach is discussed. Conclusion: It is concluded that besides current technical advancements in various aspects of causal engineering, an overarching lifecycle framework that integrates these methods into organizational practices is missing. Although diverse skills from adjacent disciplines are widely available, guidance on how to transfer these assets into causality-driven practices still need to be addressed in the published literature. CausalOps’ aim is to set a baseline for the adoption of causal methods in practical applications within interested organizations and the causality community. KW - Causal engineering KW - Model lifecycle KW - MLOps KW - Causal graphical models Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-73350 SN - 0950-5849 N1 - Corresponding author der OTH Regensburg: Robert Maier PB - Elsevier ER - TY - CHAP A1 - Staufer, Susanne A1 - Hauser, Florian A1 - Ezer, Timur A1 - Grabinger, Lisa A1 - Nadimpalli, Vamsi Krishna A1 - Röhrl, Simon A1 - Bugert, Flemming A1 - Bittner, Dominik A1 - Mottok, Jürgen T1 - EVALUATION OF THE LEARNING MANAGEMENT SYSTEM PYTHIA T2 - EDULEARN Proceedings: 16th International Conference on Education and New Learning Technologies, Palma, Spain. 1-3 July, 2024 N2 - Learning management systems gain importance due to the Corona pandemic. To personalize such a learning management system, a Moodle adaption named Pythia was created. Pythia is implemented as a Moodle plugin solution. The possibility of generating learning paths with various algorithms and the change of the graphical user interface is significant. Learning paths are generated with two different algorithms. Nestor algorithm generates learning paths with a Bayesian network, while Tyche algorithm uses a Markov model. The graphical user interface is adapted to the generated learning paths where learning element symbols are customized and the individual learning paths are depicted. This paper presents the results of a qualitative survey among German students with the aim of evaluating the first version of the learning management system Pythia. 25 students took the subject “Software Engineering for Safe and Secure Systems” in the winter term of 2023/24. The 68 asked questions focus on usage behavior, graphical user interface, usability, preferences, volume, and quality of learning elements, and learning paths. Our Moodle course for the lecture contains seven sections, each section has minimum one subsection on which the learning path is calculated. Last three sections are designed by presenting minimum one learning element of each learning element category except the collaboration tool. In a previous work, ten learning element categories were designed and evaluated comprising manuscript, brief overview, learning goal, quiz, exercise, summary, three types of additional material, and collaboration tool. The first sections are left as they are initially designed by the lecturer (normal section). The survey considers the difference between normal sections and diverse sections. Furthermore, the generated learning paths are evaluated. 13 students undertook Nestor learning paths, whereas 12 undertook Tyche learning paths. The results suggest that for the majority of students, the learning element symbols are well-chosen. Moreover, all students wish the elements relevant to the exam to be labelled. 23 students are overwhelmed by the number of learning elements in the last sections of the Moodle course. In the future, some suggestions will be implemented such as the labelling of exam relevant learning elements. To overcome the overload of learning elements, a strategy could be developed like hiding learning elements not preferred by the learning path algorithm. KW - Learning management system (LMS) KW - questionnaire (study) KW - learning elements KW - learning paths KW - usability KW - graphical user interface (GUI) KW - Moodle KW - higher education area (HEA) Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-73474 SN - 2340-1117 SP - 9089 EP - 9098 PB - IATED ER - TY - CHAP A1 - Grabinger, Lisa A1 - Mottok, Jürgen T1 - On selecting hypothesis tests for group differences T2 - ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain N2 - Deciding on the right method of analyzing empirical research data can be difficult – especially when it comes to choosing specific methods of inferential statistics, where there is often not one right way, but a variety of valid options (e.g., using an ANOVA or its non-parametric alternative for data that is not perfectly normally distributed). Novice researchers not only lack the experience to know when a particular hypothesis test is appropriate, but struggle to find suitable literature to familiarize themselves (i.e., literature that is not too superficial, yet comprehensible). With the present article we provide a remedy following the didactic method of scaffolding: We present a systematization of the most elementary inferential statistical methods, namely hypothesis tests for group differences. We start by explaining basic terms (e.g., independent variable) and then give step-by-step instructions for choosing a proper hypothesis test based on data properties, implementing it from scratch, and reporting or interpreting its results. With these practical cookbook-like guidelines, this article serves as a concise starting point for young researchers entering the field of empirical research, as a valuable resource for their instructors, and as a basis for automating statistical procedures in a software system. KW - empirical research KW - data analysis KW - inferential statistics KW - guidelines Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-78200 SP - 702 EP - 712 PB - IATED ER - TY - JOUR A1 - Grabinger, Lisa A1 - Hauser, Florian A1 - Mottok, Jürgen T1 - On the perception of graph layouts JF - Journal of Software: Evolution and Process N2 - In the field of software engineering, graph-based models are used for a variety of applications. Usually, the layout of those graphs is determined at the discretion of the user. This article empirically investigates whether different layouts affect the comprehensibility or popularity of a graph and whether one can predict the perception of certain aspects in the graph using basic graphical laws from psychology (i.e., Gestalt principles). Data on three distinct layouts of one causal graph is collected from 29 subjects using eye tracking and a print questionnaire. The evaluation of the collected data suggests that the layout of a graph does matter and that the Gestalt principles are a valuable tool for assessing partial aspects of a layout. KW - causal graphs KW - eye tracking KW - gestalt principles KW - graph layouts KW - modeling languages Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-62973 N1 - Corresponding author: Lisa Grabinger PB - Wiley ER - TY - CHAP A1 - Staufer, Susanne A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Ezer, Timur A1 - Röhrl, Simon A1 - Mottok, Jürgen T1 - Learning elements in LMS - a survey among students T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - In higher education, improving learning and learning success are goals of general improvement. Lecturers teaches content and students acquire that content in an efficient way. To structure content, learning element categories are evaluated from the student's point of view in higher education area. The aim is to validate given definitions of ten learning element categories within a Learning Management System (LMS). This paper evaluates a categorization of learning elements for organizing learning content in online education within LMSs. Therefore, ten categories of learning elements and corresponding definitions were defined in a previous work as base for this paper. The learning elements to examine are manuscript, exercise, quiz, brief overview, learning goal, summary, collaboration tool, auditory additional material, textual additional material, and visual additional material. To validate the definitions and to get improvements to each learning element a survey is processed. Beside the demographic data questions, the survey consists of two questions to the acceptance of the definitions and asks for improvements. 148 students between the ages 19 and 35 participate in the survey in summer term 2023. The education level of the participants ranges from undergraduates to Ph.D. students. The results of this paper are that more than 80% accept the given definitions. Some definitions of the learning elements are changed, but the changes are restricted to additions of maximal four words. This categorization of learning elements could lead to improvements in learning by giving the content more structure. With the structure students get the possibility to learn with preferred learning elements which could lead to more success in learning and to a decreasing dropout rate in universities. In the future, the learning elements allow to classify content within LMSs with the goal of generating individual learning paths. Furthermore, our project will integrate these learning elements, use them to generate learning paths, and could set a new standard in the way of personalized learning. KW - Learning elements KW - learning management system KW - learning objects KW - questionnaire KW - higher education area KW - content organization Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-71135 SN - 978-84-09-59215-9 SN - 2340-1079 SP - 4224 EP - 4231 PB - IATED ER - TY - CHAP A1 - Grabinger, Lisa A1 - Ezer, Timur A1 - Hauser, Florian A1 - Mottok, Jürgen T1 - The impact of eyenalyzer T2 - ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain N2 - Empirical research poses numerous challenges for beginners. This is especially true for data analysis – a task that usually requires knowledge from two distinct areas: statistics and programming. To support prospective researchers with that task, we developed a web-based tool called eyenalyzer. It supports common activities in the data analysis phase of empirical studies in a way that is suitable for novices in both, statistics and programming. The present article describes a controlled experiment investigating the impact of this tool with a total of 20 participants. All of them are given a set of common data analysis tasks. Half of the participants complete the tasks using eyenalyzer, the other half can use anything except for eyenalyzer. For each task and participant, we record the time in minutes, the task score, and the perceived difficulty. The results confirm that our tool is a valuable support for novice researchers: With eyenalyzer, the participants are significantly faster, achieve higher scores, and perceive the tasks to be less difficult. KW - tool evaluation KW - data analysis KW - eye tracking KW - empirical research Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-78215 SN - 978-84-09-63010-3 SN - 2340-1095 SP - 695 EP - 701 PB - IATED ER - TY - JOUR A1 - Scharfenberg, Georg A1 - Mottok, Jürgen A1 - Artmann, Christina A1 - Hobelsberger, Martin A1 - Paric, Ivan A1 - Großmann, Benjamin A1 - Pohlt, Clemens A1 - Wackerbarth, Alena A1 - Pausch, Uli A1 - Heidrich, Christiane A1 - Fadanelli, Martin A1 - Elsner, Michael A1 - Pöcher, Daniel A1 - Pittroff, Lenz A1 - Beer, Stefan A1 - Brückl, Oliver A1 - Haslbeck, Matthias A1 - Sterner, Michael A1 - Thema, Martin A1 - Muggenthaler, Nicole A1 - Lenck, Thorsten A1 - Götz, Philipp A1 - Eckert, Fabian A1 - Deubzer, Michael A1 - Stingl, Armin A1 - Simsek, Erol A1 - Krämer, Stefan A1 - Großmann, Benjamin A1 - Schlegl, Thomas A1 - Niedersteiner, Sascha A1 - Berlehner, Thomas A1 - Joblin, Mitchell A1 - Mauerer, Wolfgang A1 - Apel, Sven A1 - Siegmund, Janet A1 - Riehle, Dirk A1 - Weber, Joachim A1 - Palm, Christoph A1 - Zobel, Martin A1 - Al-Falouji, Ghassan A1 - Prestel, Dietmar A1 - Scharfenberg, Georg A1 - Mandl, Roland A1 - Deinzer, Arnulf A1 - Halang, W. A1 - Margraf-Stiksrud, Jutta A1 - Sick, Bernhard A1 - Deinzer, Renate A1 - Scherzinger, Stefanie A1 - Klettke, Meike A1 - Störl, Uta A1 - Wiech, Katharina A1 - Kubata, Christoph A1 - Sindersberger, Dirk A1 - Monkman, Gareth J. A1 - Dollinger, Markus A1 - Dembianny, Sven A1 - Kölbl, Andreas A1 - Welker, Franz A1 - Meier, Matthias A1 - Thumann, Philipp A1 - Swidergal, Krzysztof A1 - Wagner, Marcus A1 - Haug, Sonja A1 - Vernim, Matthias A1 - Seidenstücker, Barbara A1 - Weber, Karsten A1 - Arsan, Christian A1 - Schone, Reinhold A1 - Münder, Johannes A1 - Schroll-Decker, Irmgard A1 - Dillinger, Andrea Elisabeth A1 - Fuchshofer, Rudolf A1 - Monkman, Gareth J. A1 - Shamonin (Chamonine), Mikhail A1 - Geith, Markus A. A1 - Koch, Fabian A1 - Ühlin, Christian A1 - Schratzenstaller, Thomas A1 - Saßmannshausen, Sean Patrick A1 - Auchter, Eberhard A1 - Kriz, Willy A1 - Springer, Othmar A1 - Thumann, Maria A1 - Kusterle, Wolfgang A1 - Obermeier, Andreas A1 - Udalzow, Anton A1 - Schmailzl, Anton A1 - Hierl, Stefan A1 - Langer, Christoph A1 - Schreiner, Rupert ED - Baier, Wolfgang T1 - Forschungsbericht 2015 T3 - Forschungsberichte der OTH Regensburg - 2015 Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-13867 SN - 978-3-00-048589-3 CY - Regensburg ER - TY - JOUR A1 - Beimler, Josef A1 - Leißl, Caroline A1 - Ebner, Lena A1 - Elsner, Michael A1 - Mühlbauer, Gerhard A1 - Kohlert, Dieter A1 - Schubert, Martin J. W. A1 - Weiß, Andreas P. A1 - Sterner, Michael A1 - Raith, Thomas A1 - Afranseder, Martin A1 - Krapf, Tobias A1 - Mottok, Jürgen A1 - Siemers, Christian A1 - Großmann, Benjamin A1 - Höcherl, Johannes A1 - Schlegl, Thomas A1 - Schneider, Ralph A1 - Milaev, Johannes A1 - Rampelt, Christina A1 - Roduner, Christian A1 - Glowa, Christoph A1 - Bachl, Christoph A1 - Schliekmann, Claus A1 - Gnan, Alfons A1 - Grill, Martin A1 - Ruhland, Karl A1 - Piehler, Thomas A1 - Friers, Daniel A1 - Wels, Harald A1 - Pflug, Kenny A1 - Kucera, Markus A1 - Waas, Thomas A1 - Schlachetzki, Felix A1 - Boy, Sandra A1 - Pemmerl, Josef A1 - Leis, Alexander A1 - Welsch, Andreas F.X. A1 - Graf, Franz A1 - Zenger, Gerhard A1 - Volbert, Klaus A1 - Waas, Thomas A1 - Scherzinger, Stefanie A1 - Klettke, Meike A1 - Störl, Uta A1 - Heyl, C. A1 - Boldenko, A. A1 - Monkman, Gareth J. A1 - Kujat, Richard A1 - Briem, Ulrich A1 - Hierl, Stefan A1 - Talbot, Sebastian A1 - Schmailzl, Anton A1 - Ławrowski, Robert Damian A1 - Prommesberger, Christian A1 - Langer, Christoph A1 - Dams, Florian A1 - Schreiner, Rupert A1 - Valentino, Piergiorgio A1 - Romano, Marco A1 - Ehrlich, Ingo A1 - Furgiuele, Franco A1 - Gebbeken, Norbert A1 - Eisenried, Michael A1 - Jungbauer, Bastian A1 - Hutterer, Albert A1 - Bauhuber, Michael A1 - Mikrievskij, Andreas A1 - Argauer, Monika A1 - Hummel, Helmut A1 - Lechner, Alfred A1 - Liebetruth, Thomas A1 - Schumm, Michael A1 - Joseph, Saskia A1 - Reschke, Michael A1 - Soska, Alexander A1 - Schroll-Decker, Irmgard A1 - Putzer, Michael A1 - Rasmussen, John A1 - Dendorfer, Sebastian A1 - Weber, Tim A1 - Al-Munajjed, Amir Andreas A1 - Verkerke, Gijsbertus Jacob A1 - Renkawitz, Tobias A1 - Haug, Sonja A1 - Rudolph, Clarissa A1 - Zeitler, Annika A1 - Schaubeck, Simon A1 - Steffens, Oliver A1 - Rechenauer, Christian A1 - Schulz-Brize, Thekla A1 - Fleischmann, Florian A1 - Kusterle, Wolfgang A1 - Beer, Anne A1 - Wagner, Bernd A1 - Neidhart, Thomas ED - Baier, Wolfgang T1 - Forschungsbericht 2013 T3 - Forschungsberichte der OTH Regensburg - 2013 Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-7990 CY - Regensburg ER - TY - JOUR A1 - Appelhans, Marie-Luise A1 - Kampmann, Matthias A1 - Mottok, Jürgen A1 - Riederer, Michael A1 - Nagl, Klaus A1 - Steffens, Oliver A1 - Dünnweber, Jan A1 - Wildgruber, Markus A1 - Roth, Julius A1 - Stadler, Timo A1 - Palm, Christoph A1 - Weiß, Martin Georg A1 - Rochholz, Sandra A1 - Bierl, Rudolf A1 - Gschossmann, Andreas A1 - Haug, Sonja A1 - Schmidbauer, Simon A1 - Koch, Anna A1 - Westner, Markus A1 - Bary, Benedikt von A1 - Ellermeier, Andreas A1 - Vögele, Daniel A1 - Maiwald, Frederik A1 - Hierl, Stefan A1 - Schlamp, Matthias A1 - Ehrlich, Ingo A1 - Siegl, Marco A1 - Hüntelmann, Sven A1 - Wildfeuer, Matthias A1 - Brückl, Oliver A1 - Sterner, Michael A1 - Hofrichter, Andreas A1 - Eckert, Fabian A1 - Bauer, Franz A1 - Dawoud, Belal A1 - Rabl, Hans-Peter A1 - Gamisch, Bernd A1 - Schmidt, Ottfried A1 - Heberl, Michael A1 - Thema, Martin A1 - Mayer, Ulrike A1 - Eller, Johannes A1 - Sippenauer, Thomas A1 - Adelt, Christian A1 - Haslbeck, Matthias A1 - Vogl, Bettina A1 - Mauerer, Wolfgang A1 - Ramsauer, Ralf A1 - Lohmann, Daniel A1 - Sax, Irmengard A1 - Gabor, Thomas A1 - Feld, Sebastian A1 - Linnhoff-Popien, Claudia A1 - Ławrowski, Robert Damian A1 - Langer, Christoph A1 - Schreiner, Rupert A1 - Sellmair, Josef ED - Baier, Wolfgang T1 - Forschung 2019 BT - Thema: Künstliche Intelligenz N2 - Bericht mit Forschungsprojekten aus verschiedenen Bereichen der OTH Regensburg mit dem Schwerpunktthema "Künstliche Intelligenz" und einem Gespräch zur "Medizin der Zukunft" T3 - Forschungsberichte der OTH Regensburg - 2019 KW - Forschung KW - Forschungsbericht KW - Künstliche Intelligenz Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-7890 SN - 978-3-9818209-7-3 CY - Regensburg ER - TY - JOUR A1 - Weber, Karsten A1 - Dendorfer, Sebastian A1 - Süß, Franz A1 - Kubowitsch, Simone A1 - Schratzenstaller, Thomas A1 - Haug, Sonja A1 - Mohr, Christa A1 - Kiesl, Hans A1 - Drechsler, Jörg A1 - Westner, Markus A1 - Kobus, Jörn A1 - Schubert, Martin J. W. A1 - Zenger, Stefan A1 - Pietsch, Alexander A1 - Weiß, Josef A1 - Hinterseer, Sebastian A1 - Schieck, Roland A1 - Scherzinger, Stefanie A1 - Klettke, Meike A1 - Ringlstetter, Andreas A1 - Störl, Uta A1 - Bissyandé, Tegawendé F. A1 - Seeburger, Achim A1 - Schindler, Timo A1 - Ramsauer, Ralf A1 - Kiszka, Jan A1 - Kölbl, Andreas A1 - Lohmann, Daniel A1 - Mauerer, Wolfgang A1 - Maier, Johannes A1 - Scorna, Ulrike A1 - Palm, Christoph A1 - Soska, Alexander A1 - Mottok, Jürgen A1 - Ellermeier, Andreas A1 - Vögele, Daniel A1 - Hierl, Stefan A1 - Briem, Ulrich A1 - Buschmann, Knut A1 - Ehrlich, Ingo A1 - Pongratz, Christian A1 - Pielmeier, Benjamin A1 - Tyroller, Quirin A1 - Monkman, Gareth J. A1 - Gut, Franz A1 - Roth, Carina A1 - Hausler, Peter A1 - Bierl, Rudolf A1 - Prommesberger, Christian A1 - Ławrowski, Robert Damian A1 - Langer, Christoph A1 - Schreiner, Rupert A1 - Huang, Yifeng A1 - She, Juncong A1 - Ottl, Andreas A1 - Rieger, Walter A1 - Kraml, Agnes A1 - Poxleitner, Thomas A1 - Hofer, Simon A1 - Heisterkamp, Benjamin A1 - Lerch, Maximilian A1 - Sammer, Nike A1 - Golde, Olivia A1 - Wellnitz, Felix A1 - Schmid, Sandra A1 - Muntschick, Claudia A1 - Kusterle, Wolfgang A1 - Paric, Ivan A1 - Brückl, Oliver A1 - Haslbeck, Matthias A1 - Schmidt, Ottfried A1 - Schwanzer, Peter A1 - Rabl, Hans-Peter A1 - Sterner, Michael A1 - Bauer, Franz A1 - Steinmann, Sven A1 - Eckert, Fabian A1 - Hofrichter, Andreas ED - Baier, Wolfgang T1 - Forschungsbericht 2017 T3 - Forschungsberichte der OTH Regensburg - 2017 KW - Forschung KW - Forschungsbericht Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-13835 SN - 978-3-9818209-3-5 CY - Regensburg ER - TY - CHAP A1 - Staufer, Susanne A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Nadimpalli, Vamsi Krishna A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Learning elements in online learning management systems T2 - Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-67725 SP - 3121 EP - 3130 PB - IATED ER - TY - CHAP A1 - Staufer, Susanne A1 - Nadimpalli, Vamsi Krishna A1 - Hauser, Florian A1 - Bittner, Dominik A1 - Grabinger, Lisa A1 - Bugert, Flemming A1 - Ezer, Timur A1 - Röhrl, Simon A1 - Mottok, Jürgen T1 - Persistence of Questionnaire Data on Learning Styles, Learning Strategies AND Personality Traits T2 - ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain N2 - In the context of learning, questionnaires are carried out to gain information about learners. This learner profile has various benefits, like adapting the learning content, promoting of self-reflection, or increasing motivation in learning and therefore better learning results. Some researchers take the results of such questionnaires as ground truth or trust them blindly. Examining how persistent questionnaires are, asking the same questions twice, and comparing the results is a way to prove or falsify this statement. Our research procedure compares the results of three different questionnaires. The first questionnaire is the ILS (index of learning styles) according to the Felder-Silverman Learning Style Model (FSLSM) with about 44 questions. Learning strategies are examined with the LIST-K questionnaire consisting of 39 questions after Klingsieck. The third and last questionnaire is about personality traits. With only ten questions, Rammstedt et al. describe the BFI-10 questionnaire for personality traits. To compare results, the same study with the three named questionnaires is carried out twice with three to four months in between. The sample includes 35 students in their bachelor studies taking the course Software Engineering in a blended learning format. After collecting the questionnaire data from the students, a comparison is made in two different ways. First, we compare the data points based on the given answers. Second, a comparison is made based on the calculated questionnaire results because each of the three questionnaires has its own analysis method. For example, the analysis method of the ILS delivers as a result four integers representing the four characteristics of a learning style, while LIST-K makes a factor analysis. The results of the paper show that both the given answers and the calculated questionnaire results differ. Not one student has given the same answer inside each questionnaire with causes, like a change of learning style, learning strategy, and personality traits, or not filling in conscientiously. KW - learning style KW - learning strategy KW - personality traits KW - questionnaire study Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-78246 SN - 978-84-09-63010-3 SN - 2340-1095 SP - 6310 EP - 6319 PB - IATED ER - TY - JOUR A1 - Röhrl, Simon A1 - Staufer, Susanne A1 - Bugert, Flemming A1 - Nadimpalli, Vamsi Krishna A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Ezer, Timur A1 - Altweck, Ricardo A1 - Graf, Sabine A1 - Kriza, Thomas A1 - Mottok, Jürgen T1 - Ethical Considerations of AI in Education: A Case Study based on Pythia Learning Enhancement System JF - IEEE Access N2 - As the use of AI in education increases, addressing ethical concerns is essential for its responsible use and implementation. This study explores the ethical considerations of AI in education by analyzing a concrete application, the Pythia Learning Enhancement System, which enables personalized and adaptive educational experiences. In this case study, the concrete implementation of Pythia, contrary to high-level abstract analyses, provides practical insights into these ethical issues. To achieve this goal, we first define Pythia and outline its implementation. Using the various topics covered by Pythia, the ethical issues associated with each of these topics are outlined, resulting in a list of ten distinct ethical issues. Because there is overlap in issues covered by similar applications, they can benefit from this identification. An ethical (human rights) and didactic (constructivism) theoretical background is then provided as a basis for further discussion. This is used to build the arguments used in the main study. This consists of analyzing each of the issues and providing recommendations to mitigate potential harm arising from these issues. This helps to provide guidelines for future applications. In the analysis, the ethical discussion is mainly based on the human rights of the stakeholders involved, emphasizing human dignity. After the analysis, each of the issues is contextualized with the recent AI Act of the European Union, providing a novel mapping of the issues of AI in education to the AI Act. Finally, the limitations of the study are stated and a plan for future research is presented. KW - Ethics KW - Artificial intelligence KW - Education KW - Stakeholders KW - Psychology KW - Privacy KW - Search problems KW - Guidelines KW - Focusing KW - Europe Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-83403 SN - 2169-3536 N1 - Corresponding author der OTH Regensburg: Simon Röhrl VL - 11 SP - 1 EP - 25 PB - Institute of Electrical and Electronics Engineers (IEEE) ER - TY - JOUR A1 - Broser, Christian A1 - Falter, Thomas A1 - Ławrowski, Robert Damian A1 - Altenbuchner, Amelie A1 - Vögele, Daniel A1 - Koss, Claus A1 - Schlamp, Matthias A1 - Dunnweber, Jan A1 - Steffens, Oliver A1 - Heckner, Markus A1 - Jaritz, Sabine A1 - Schiegl, Thomas A1 - Corsten, Sabine A1 - Lauer, Norina A1 - Guertler, Katherine A1 - Koenig, Eric A1 - Haug, Sonja A1 - Huber, Dominik A1 - Birkenmaier, Clemens A1 - Krenkel, Lars A1 - Wagner, Thomas A1 - Justus, Xenia A1 - Saßmannshausen, Sean Patrick A1 - Kleine, Nadine A1 - Weber, Karsten A1 - Braun, Carina N. A1 - Giacoppo, Giuliano A1 - Heinrich, Michael A1 - Just, Tobias A1 - Schreck, Thomas A1 - Schnabl, Andreas A1 - Gilmore, Amador Téran A1 - Roeslin, Samuel A1 - Schmid, Sandra A1 - Wellnitz, Felix A1 - Malz, Sebastian A1 - Maurial, Andreas A1 - Hauser, Florian A1 - Mottok, Jürgen A1 - Klettke, Meike A1 - Scherzinger, Stefanie A1 - Störl, Uta A1 - Heckner, Markus A1 - Bazo, Alexander A1 - Wolff, Christian A1 - Kopper, Andreas A1 - Westner, Markus A1 - Pongratz, Christian A1 - Ehrlich, Ingo A1 - Briem, Ulrich A1 - Hederer, Sebastian A1 - Wagner, Marcus A1 - Schillinger, Moritz A1 - Görlach, Julien A1 - Hierl, Stefan A1 - Siegl, Marco A1 - Langer, Christoph A1 - Hausladen, Matthias A1 - Schreiner, Rupert A1 - Haslbeck, Matthias A1 - Kreuzer, Reinhard A1 - Brückl, Oliver A1 - Dawoud, Belal A1 - Rabl, Hans-Peter A1 - Gamisch, Bernd A1 - Schmidt, Ottfried A1 - Heberl, Michael A1 - Gänsbauer, Bianca A1 - Bick, Werner A1 - Ellermeier, Andreas A1 - Monkman, Gareth J. A1 - Prem, Nina A1 - Sindersberger, Dirk A1 - Tschurtschenthaler, Karl A1 - Aurbach, Maximilian A1 - Dendorfer, Sebastian A1 - Betz, Michael A. A1 - Szecsey, Tamara A1 - Mauerer, Wolfgang A1 - Murr, Florian ED - Baier, Wolfgang T1 - Forschung 2018 T3 - Forschungsberichte der OTH Regensburg - 2018 KW - Forschung KW - Forschungsbericht Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-13826 SN - 978-3-9818209-5-9 CY - Regensburg ER - TY - JOUR A1 - Rück, Thomas A1 - Bierl, Rudolf A1 - Lechner, Alfred A1 - Graf, Antonia A1 - Dams, Florian A1 - Schreiner, Rupert A1 - Auchter, Eberhard A1 - Kriz, Willy A1 - Deubzer, MIchael A1 - Schiller, Frank A1 - Mottok, Jürgen A1 - Niemetz, Michael A1 - Margull, Ulrich A1 - Hagel, Georg A1 - Utesch, Matthias A1 - Waldherr, Franz A1 - Böhm, Matthias A1 - Fraunhoffer, Judith A1 - Gardeia, Armin A1 - Schneider, Ralph A1 - Streubel, Janet A1 - Landes, Dieter A1 - Studt, Reimer A1 - Peuker, Dominik A1 - Scharfenberg, Georg A1 - Hook, Christian A1 - Schuster, Dietwald A1 - Ehrlich, Ingo A1 - Dinnebier, Heinrich A1 - Briem, Ulrich A1 - Lämmlein, Stephan A1 - Koder, Alexander A1 - Bialek, Adam A1 - Genewsky, Axel A1 - Neumeier, Michael A1 - Schlosser, Philipp A1 - Rabl, Hans-Peter A1 - Paule, Matthias A1 - Galster, Christoph A1 - Schiedermeier, Michael A1 - Zwickel, Andreas A1 - Hobmeier, Christoph A1 - Bischoff, Tobias A1 - Rill, Georg A1 - Schaeffer, Thomas A1 - Arbesmeier, Martin A1 - Groß, Andreas A1 - Schlegl, Thomas A1 - Becker, Mark A1 - Senn, Konrad A1 - Schliekmann, Claus A1 - Scholz, Peter A1 - Sippl, Christian A1 - Grill, Martin ED - Eckstein, Josef T1 - Forschungsbericht 2011 / Hochschule für Angewandte Wissenschaften - Fachhochschule Regensburg T3 - Forschungsberichte der OTH Regensburg - 2011 Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-7321 SN - 1868-3533 CY - Regensburg ER - TY - CHAP A1 - Staufer, Susanne A1 - Bugert, Flemming A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Ezer, Timur A1 - Nadimpalli, Vamsi Krishna A1 - Bittner, Dominik A1 - Röhrl, Simon A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Tyche algorithm: Markov models for generating learning paths in learning management systems T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - In the intricate tapestry of the cosmos, where celestial threads weave stories of destiny, an enigmatic deity stands at the intersection of chance and fate — Tyche, the goddess of fortune. In science and probability, coincidence plays a distinctive role in Bayesian Networks (BNs) and Markov Models (MMs). This paper introduces the Tyche algorithm named after the goddess of fortune. The Tyche algorithm is a Markov model designed to generate learning paths in Learning Management Systems (LMSs). A learning path is a type of individualization that personalises the order of learning elements within an LMS course. Learning elements are fundamental components within an LMS course, depicting the learning content in diverse ways. In our case, the learning path tailoring is based on the learner’s learning style according to Felder-Silverman Learning Style Model (FSLSM) – an indicator for the ideal pathway and learning element for the learner’s optimum learning. The Tyche algorithm offers the advantage to provide students the most suitable learning path. Tyche is a MM structure with various matrices containing transition probabilities depending on the learning style. Nine categories of learning elements defined in a previous survey form the basis of the node structure of the MM. For a generic approach, a survey was designed to obtain the transition probabilities depending on the individual learning style. The survey with more than 100 German students participated is processed with the tool LimeSurvey. Students are asked about their learning style using the Index of Learning Styles (ILS) questionnaire according to Felder-Silverman and about the percentage probabilities of learning elements to get their individual sequence as learning path. The percentages are queried in two different ways. Firstly, the students were asked to provide a sequence of learning elements within each position of the sequence filled with probabilities for all learning elements. Secondly, a learning element is given and the students are asked to indicate which learning element they would work on next. The first way of asking for the probabilities is used to find the start node in the MM, whereas the second approach forms the probability matrices between the nodes within the MM. As result of the survey, the Tyche algorithm presents generic transition probabilities. It improves the learning process of individuals only by asking for their learning style: it generates individual learning paths through the learning elements within an LMS based on the MM explained above by solely getting the answers of the ILS questionnaire as input. In the future, other questionnaires such as BFI-10 for personality traits or LIST-K for learning strategies may offer a more comprehensive input. However, the next step is to evaluate Tyche with about 25 students in a software engineering lecture. This is planned for the year 2024. KW - Markov model KW - learning style KW - learning elements KW - learning management system KW - higher education area Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-71148 SN - 978-84-09-59215-9 SN - 2340-1079 SP - 4195 EP - 4205 PB - IATED Academy ER - TY - CHAP A1 - Staufer, Susanne A1 - Ezer, Timur A1 - Röhrl, Simon A1 - Grabinger, Lisa A1 - Hauser, Florian A1 - Nadimpalli, Vamsi Krishna A1 - Antoni, Erika A1 - Mottok, Jürgen A1 - Schaffer, Josefa T1 - TYCHE ALGORITHM 2.0: Learning Paths from Questionnaire Responses and Learning Analytics T2 - ICERI2025 Proceedings N2 - The digitalization of learning processes has increased the need for adaptive learning paths tailored individually to learners. A novel algorithm for learning path generation is presented in this paper, namely Tyche 2.0. It extends the original Tyche approach after Staufer et al. – a Markov model for generating learning paths – by integrating additional learner data beyond learning styles (Index of Learning Styles (ILS)), including learning strategies (LIST-K questionnaire), personality traits (BFI-10 questionnaire), and learning analytics captured through screen recordings. In order to be able to use the screen recordings, a heuristic evaluates them. Furthermore, this enhanced algorithm employs Markov models to dynamically generate personalized learning paths. These are based on both questionnaire responses and real-time engagement data, the weights of which undergo dynamic adjustment over time. We made a small evaluation of Tyche 2.0 without the learning analytics influence, which shows that there is room for further improvements. Future research will focus on evaluating whole Tyche 2.0 in another university setting to further improve personalization and user engagement. KW - Markov model KW - Learning paths KW - Learning style KW - Learning strategy KW - Personality traits KW - Learning analytics Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-87846 SN - 978-84-09-78706-7 SP - 2562 EP - 2572 PB - IATED ER -