TY - INPR A1 - Linz, Tilo A1 - Mottok, Jürgen T1 - Application of Causal Models in Scenario-based Testing N2 - This paper presents a new methodology for scenario-based testing of automated driving functions in the context of ISO 21448 (safety of the target function). By using structural causal models (SCMs), the evaluation process of highly automated vehicle systems is to be improved, thus increasing their safety and reliability. Using SCMs, the presented methodology systematically analyzes causal relationships between various risk factors of the investigated system and its operating environment and automatically identifies potential parameter combinations that influence system safety. This approach makes it possible to safeguard automated driving functions, such as an emergency brake assistant, by determining foreseeable risks and providing them as test parameters for relevant scenarios. The HolmeS3 approach combines expert knowledge with probabilistic data analysis to develop robust causal models that can be validated through both simulation and real-world testing. The use of causal inference enables the generation of critical test cases, known as "edge and corner cases", which are essential for testing vehicle systems under investigation. This focused testing approach helps to limit the test case explosion that occurs with conventional approaches by specifically identifying highly relevant parameter combinations that potentially (negatively) influence system performance. The methodology presented, which was developed as part of the HolmeS3 R&D project, offers transparency, comparability, explainability and traceability in the modeling and testing processes. It supports compliance with the ISO 21448 standard and lays the foundation for the causality-driven development of safe and reliable automotive technology. The project's tools and methods can be applied beyond the automotive sector to all cyber-physical systems that require rigorous safety validation. Y1 - 2024 U6 - https://doi.org/10.13140/RG.2.2.34160.06402 ER - TY - CHAP A1 - Frauenschläger, Tobias A1 - Mottok, Jürgen T1 - Problems and New Approaches for Crypto-Agility in Operational Technology T2 - 12th European Congress Embedded Real Time Systems (ERTS 2024), 11-12 June 2024, Toulouse, France N2 - In recent years, cybersecurity has also become relevant for Operational Technology (OT). Critical systems like industrial automation systems or transportation systems are faced with new threats, and therefore require the implementation of thorough security measures. Regulations further mandate the deployment and regular verification of these security measures. However, OT systems differ from well-known systems of classic Information Technology (IT), such as mission times spanning decades, infrequent updates only during on-site maintenance, or diverse devices with varying support for security measures. The growing field of crypto-agility examines approaches to integrate security measures in an agile and flexible way, making updates easier and, therefore, encouraging a more frequent deployment of them. This paper contributes to this research field in the context of secure communication in two ways. We first examine the current state of crypto-agility by providing an overview of existing measures for OT systems. Then, we propose a new architecture concept with different deployment approaches to integrate security measures in a crypto-agile way. Based on a security library with a generic interface and a flexible proxy application, our architecture is capable of securing both new OT systems and existing ones via retrofit. Y1 - 2024 UR - https://www.researchgate.net/publication/383709526_Problems_and_New_Approaches_for_Crypto-Agility_in_Operational_Technology ER - TY - CHAP A1 - Schwind, Philipp A1 - Frauenschläger, Tobias A1 - Mottok, Jürgen T1 - Implementation of a Bump-in-the-Wire Security Gateway T2 - Proceedings of the 12th Prague Embedded Systems Workshop, June 27 - 29, 2024, Horoměřice, Czech Republic N2 - In the face of escalating cyber threats, the integration of Operational Technology (OT) with Information Technology (IT) systems presents heightened vulnerabilities to critical infrastructures. This paper focuses on the need for cybersecurity, showcasing the design and implementation of a security gateway to achieve bump-in-the-wire security between two units to be protected (assets). For that, each asset is assigned one security module that safeguards its communication paths. To ease bump-in-the-wire capability, the communication between the asset and the security-gateway must be stateless and operate on OSI layer 2. This is necessary to safeguard the whole communication bandwidth, regardless of the used protocols. For this objective, Linux-based packet sockets are used. An encrypted tunnel is established between two security gateways using the Datagram Transport Layer Security (DTLS) protocol. The results show that the implemented solution is capable of securing the asset’s network traffic without the need of any modifications. Y1 - 2024 UR - https://pesw.fit.cvut.cz/2024/PESW_2024.pdf SN - 978-80-01-07303-2 SP - 26 EP - 35 ER - TY - CHAP A1 - Horn, Luca A1 - Frauenschläger, Tobias A1 - Mottok, Jürgen T1 - Integration and Evaluation of Different FPGA based Hardware Accelerators for the AES Algorithm in the TLS Protocol to be Used in Critical Automation Systems T2 - 4. Symposium Elektronik und Systemintegration, Tagungsband: Symposium am 17. April 2024 Hochschule Landshut N2 - This thesis addresses the challenges of hardware-assisted cryptography in the context of automation systems in critical infrastructures. While hardware accelerators enhance cryptographic calculations in both performance and security, their permanence poses issues in adapting to evolving security concerns. To overcome this problem, we integrated and evaluated a hardware accelerator for the AES algorithm on an FPGA within a TLS application, comparing its performance with other accelerators. Employing a hybrid FPGA-CPU processor system, this setup achieves over 800 Mbit/s data rates, showcasing a more than 27 times acceleration in TLS transmissions compared to purely software-based solutions. The FPGA's flexibility and upgradability therefore make it an ideal platform for critical infrastructure, ensuring longevity and superior acceleration in TLS data transfers. Y1 - 2024 UR - https://www.haw-landshut.de/static/ITZ/Bilder/Cluster_MST/ESI_Symposium/ESI_2024/Tagungsband/1B2_Frauenschlaeger_OTH-R_TB-ESI2024_s18-27.pdf SN - 978-3-9818439-9-6 SP - 18 EP - 27 PB - Hochschule Landshut CY - Landshut ER - TY - CHAP A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Mottok, Jürgen A1 - Gruber, Hans T1 - Visual Expertise in Code Reviews: Using Holistic Models of Image Perception to Analyze and Interpret Eye Movements T2 - ETRA '23: 2023 Symposium on Eye Tracking Research and Applications, Tubingen Germany 30 May 2023- 2 June 2023 N2 - This study uses holistic models of image perception to analyze and interpret eye movements during a code review. 23 participants (15 novices and 8 experts) take part in the experiment. The subjects’ task is to review six short code examples in C programming language and identify possible errors. During the experiment, their eye movements are recorded by an SMI 250 REDmobile. Additional data is collected through questionnaires and retrospective interviews. The results implicate that holistic models of image perception provide a suitable theoretical background for the analysis and interpretation of eye movements during code reviews. The assumptions of these models are particularly evident for expert programmers. Their approach can be divided into different phases with characteristic eye movement patterns. It is best described as switching between scans of the code example (global viewing) and the detailed examination of errors (focal viewing). Y1 - 2023 U6 - https://doi.org/10.1145/3588015.3589189 SP - 1 EP - 7 PB - ACM ER - TY - JOUR A1 - Pozzobon, Enrico A1 - Weiß, Nils A1 - Mottok, Jürgen A1 - Matoušek, Václav T1 - An evolutionary fault injection settings search algorithm for attacks on safe and secure embedded systems JF - Neural Network World (NNW) Y1 - 2023 U6 - https://doi.org/10.14311/NNW.2023.33.020 VL - 33 IS - 5 SP - 357 EP - 374 PB - Czech Technical University in Prague ER - TY - CHAP A1 - Füreder, Lukas A1 - Mottok, Jürgen T1 - Assessment of a MACsec-based Security System for Use in Critical Infrastructure Communication T2 - Proceedings of the 12th Prague Embedded Systems Workshop, June 27 - 29, 2024, Horoměřice, Czech Republic N2 - This paper investigates the integration of Media Access Control Security (MACsec) into the communication of critical infrastructure, specifically within power grid applications, such as Substation Automation Systems (SAS) using the IEC 61850 standard. Building on the principles of both standards, this study aims to determine if MACsec can meet the security and performance requirements set by IEC 62351 for power system communications. Furthermore, a test environment containing a number of Intelligent Electronic Devices (IEDs) supporting communication compliant to all IEC 61850 message types is established to evaluate this integration. The results of the measurements executed in this environment indicate that MACsec could secure all types of messages, such as Manufacturing Message Specification (MMS), Sampled-Value (SV) and Generic Object Oriented Substation Events (GOOSE), within the required time periods without significant delays. Even with additional encryption activated in the cipher suite, the resulting transmission times are well below the required times. This suggests that MACsec can enhance the security goals for industrial communication by providing confidentiality in addition to the already mandated assurance of authenticity and integrity to all messages without compromising performance. Only the requirement for end-to-end security cannot be met by MACsec in this configuration, as the security system re-encrypts with every hop of the transmission. For this reason, we propose a hybrid approach of Transport Layer Security (TLS) and MACsec as part of future work. KW - MACsec KW - IEC61850 KW - IEC62351 KW - GOOSE KW - Secure Communication Y1 - 2024 UR - https://pesw.fit.cvut.cz/2024/PESW_2024.pdf SN - 978-80-01-07303-2 SP - 51 EP - 59 ER - TY - CHAP A1 - Bittner, Dominik A1 - Hendricks, Ricky-Ricardo A1 - Horn, Luca A1 - Mottok, Jürgen T1 - In-depth Benchmarking of Transfer Learning Techniques for Improved Bottle Recognition T2 - 2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS), Guayaquil, Ecuador, 04-07 July 2023 N2 - An immense diversity in bottle types requires high accuracy during sorting for recycling purposes by breweries. This extremely complex and time-consuming procedure can result in enormous additional costs for them. This paper presents transfer learning-based algorithms for classifying beer bottle brands using camera images, applicable in individual sorting solutions for different use cases. The problem is tackled using customised EfficientNet, InceptionResNet and VGG models along with an augmented dataset. In addition, a detailed analysis of different model and parameter combinations is performed, enabling tailor-made technologies for specific conditions and resource limitations. In accompanying validations and subsequent tests, a test accuracy of 100% in the recognition of beer brands could be achieved, proving the proposed method fully contributes to the solution of the problem. KW - Analytical models KW - Costs KW - Transfer learning KW - Benchmark testing KW - Cameras KW - Pattern recognition KW - Recycling Y1 - 2023 SN - 979-8-3503-3337-4 U6 - https://doi.org/10.1109/ICPRS58416.2023.10178995 SP - 1 EP - 6 PB - IEEE ER - TY - CHAP A1 - Röhrl, Simon A1 - Staufer, Susanne A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Bugert, Flemming A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Ezer, Timur A1 - Mottok, Jürgen T1 - PYTHIA - AI SUGGESTED INDIVIDUAL LEARNING PATHS FOR EVERY STUDENT T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - During the COVID-19 pandemic, the importance of digital course rooms, where teachers provide their learning materials, increased dramatically. While these platforms are crucial for providing teaching materials, they often fall short in addressing individual student needs. A system within an academic setting, capable of creating and presenting individual learning paths for each student, can solve these issues. These paths are composed of various learning elements - defined in our previous work as units of educational content with which a learner works. Currently, there is no suitable system that enables the integration of learning path generating algorithms into a digital course room. Therefore we present an application that enables this integration into the Moodle Learning Management System (LMS). More precisely, this paper presents a Moodle plugin together with its framework. It describes the mechanism for effectively collecting data from Moodle, which AI algorithms then use to generate personalized learning paths. Subsequently these paths are visualized with the help of the Moodle plugin. We started with a set of requirements and use cases for the interface connecting Moodle to the AI system, which were established with a group of experts. Based on the requirements, various relevant technologies were assessed, and the best ones were chosen for implementation. Following that, the paper develops a strategy for software structuring as well as an architecture, focusing on performance, modularity, and ease of deployment for widespread use. Furthermore, the architecture ensures a simple method for integrating the algorithms. Afterwards, the framework's concrete implementation is described. A technique for enriching learning elements with metadata is presented, and additionally a concept for presenting these learning elements within a hierarchy. Moreover, it is shown how questionnaire responses and learning analytics are utilized for data collection. We cover in detail techniques for extracting and storing data from the Moodle database, as well as methods for customizing Moodle course rooms and a standard API for incorporating AI algorithms. Finally, the paper discusses the application of the proposed framework in an actual course and how student feedback is collected, which could enhance the framework. It concludes with an assessment of the outcomes obtained and prospects for the framework's future advancements. KW - Personalized Learning Paths KW - Learning Management System KW - Software Architecture KW - Moodle KW - Artificial Intelligence Y1 - 2024 SN - 978-84-09-59215-9 U6 - https://doi.org/10.21125/inted.2024.0783 SN - 2340-1079 SP - 2871 EP - 2880 ER - TY - JOUR A1 - Fuxen, Philipp A1 - Schönhärl, Stefan A1 - Schmidt, Jonas A1 - Gerstner, Mathias A1 - Jahn, Sabrina A1 - Graf, Julian A1 - Hackenberg, Rudolf A1 - Mottok, Jürgen T1 - A Cybersecurity Education Platform for Automotive Penetration Testing JF - International Journal On Advances in Security N2 - The paper presents a penetration testing framework for automotive IT security education and evaluates its realization. The automotive sector is changing due to automated driving functions, connected vehicles, and electric vehicles. This development also creates new and more critical vulnerabilities. This paper addresses a possible countermeasure, automotive IT security education. Some existing solutions are evaluated and compared with the created Automotive Penetration Testing Education Platform (APTEP) framework. In addition, the APTEP architecture is described. It consists of three layers representing different attack points of a vehicle. The realization of the APTEP is a hardware case and a virtual platform referred to as the Automotive Network Security Case (ANSKo). The hardware case contains emulated control units and different communication protocols. The virtual platform uses Docker containers to provide a similar experience over the internet. Both offer two kinds of challenges. The first introduces users to a specific interface, while the second combines multiple interfaces, to a complex and realistic challenge. This concept is based on modern didactic theories, such as constructivism and problem-based/challenge-based learning. Computer Science students from the Ostbayerische Technische Hochschule (OTH) Regensburg experienced the challenges as part of a elective subject. In an online survey evaluated in this paper, they gave positive feedback. Also, a part of the evaluation is the mapping of the ANSKo and the maturity levels in the Software Assurance Maturity Model (SAMM) practice Education & Guidance as well as the SAMM practice Security Testing. The scientific contribution of this paper is to present an APTEP, a corresponding learning concept and an evaluation method. KW - Challenge-based Learning KW - Education Framework KW - Penetration Testing KW - Automotive KW - IT-Security Education Y1 - 2022 UR - http://www.iariajournals.org/security/sec_v15_n34_2022_paged.pdf SN - 1942-2636 VL - 15 IS - 3&4 SP - 106 EP - 118 PB - IARIA 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 - CHAP A1 - Jahn, Sabrina A1 - Weiss, Nils A1 - Akcakoca, Ugur A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - López Martínez, A. ED - Candel Torres, I. T1 - Under The Hood - A Concept for Virtualized Automotive Security Education T2 - EDULEARN21: Proceedings, 13th International Conference on Education and New Learning Technologies, Online Conference. 5-6 July, 2021 N2 - In recent years, our society faced a massive interconnection of computer-based everyday objects, which opens these items for cyber-attacks. Dependent on the physical capabilities, successful attacks can vary from data exposure or a loss of functionality to a threat to life and limb. Connected- and autonomous vehicles are extremely safety-critical systems with a huge damage potential. This global trend, together with existing and upcoming regulations (ISO 270xx, ISO 21434, UNECE WP.29, UNECE R155), and the lack of qualified professionals create a tension field for the entire automotive industry. Hence, new education concepts for engineers of safety-critical and connected systems are necessary to secure our daily and future systems against cyber-attacks and raise awareness and knowledge of the topic of IT-Security. Existing automotive security education systems have one common problem: All systems are hardware-based and therefore have very steep learning curves for beginners. Hardware-based systems, in general, are expensive in their initial costs, require regular maintenance, and add diverse operational difficulties independent of the aspired education goal. Additionally, the global pandemic increased the necessity of virtual education concepts for security training in cyber-physical systems. Therefore, we present a novel concept for the education of cyber-security professionals for automotive systems based on discovery and problem-based learning in a virtual learning environment (VLE). Our concept contains individual exercises focusing on the topics of vulnerabilities and attacks in automotive networks and systems. Each exercise relates those topics to the corresponding security goals and countermeasures for mitigation. The learners work collaboratively in a self-contained manner within the VLE to acquire the necessary information to answer questions or find a solution to the given problem. To consider the heterogeneous background (e.g. knowledge, experience, preconceptions) of the learners, the topics can be presented in different difficulties, enabling an adaptable learning environment and different learning trajectories within the exercises. The concept is based on a VLE, consisting of automotive networks and components, which simulate the behavior of a vehicle. This environment provides a hands-on, "real-life" scenario, which allows discovery and problem-based learning in a realistic, but cheap and scalable education environment. Furthermore, virtualization removes common difficulties, always present in training on real hardware. This aims to decrease complexity, prevent learning obstacles related to hardware handling, and enables a location-independent learning environment. The target group of our education concept is Bachelor and Master students of computer science, engineering (e.g. electrical engineering, mechatronics), or similar studies, and (experienced) engineers from the industry. In summary, our publication contains two contributions. We present an adaptable virtual learning environment for automotive security education, combined with an educational concept based on discovery and problem-based learning techniques. The goals of our concept are the education of cyber-security professionals for safety-critical, connected automotive systems and the support of life-long learning reaching from academic education to training in the industry. KW - automotive systems KW - discovery learning KW - higher education KW - inductive teaching KW - problem-based learning KW - security education KW - virtual learning environment Y1 - 2021 SN - 978-84-09-31267-2 U6 - https://doi.org/10.21125/edulearn.2021.1231 SN - 2340-1117 SP - 6109 EP - 6118 ER - TY - CHAP A1 - Ezer, Timur A1 - Grabinger, Lisa A1 - Hauser, Florian A1 - Staufer, Susanne A1 - Mottok, Jürgen T1 - EYE TRACKING AS TECHNOLOGY IN EDUCATION: FURTHER INVESTIGATION OF DATA QUALITY AND IMPROVEMENTS T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - Eye tracking serves as a powerful tool across a variety of empirical research areas: From usability research over cognitive research to educational research and applications in classrooms. However, data noise in eye tracking data poses a challenge to researchers and educators, as it leads to gaze positions being measured imprecisely under unfavorable conditions. In our previous study, we systematically investigated factors that influence data quality and are easily controllable in a classroom or laboratory environment, such as illumination, sampling frequency, and head orientation. However, no recommendations regarding the light source and light orientation could be provided, as these influences could not be analyzed in sufficient detail. Yet, a further examination of these factors, eliminating human influences by using an artificial head, revealed significant differences between individual settings. Hence, in this empirical study of eye tracking as an educational technology, we delve deeper into examining the impact of both light source and light orientation on data quality. This is investigated with an artificial head together with the Tobii Pro Spectrum eye tracking device. To measure data quality, we use the metrics precision and standard deviation as indicators of data noise. The obtained results derive practical advice for educators and researchers, such as not to illuminate the subject from the rear, in order to gather useful data for research and future classroom applications. Thereby, this study serves as a complement to our previous research, answering open questions regarding best practices for researchers and educators when using eye trackers. It aims to provide valuable insights into producing data of the highest quality possible when using eye trackers, both in laboratory settings and in future classrooms applications. KW - Eye tracking KW - data quality KW - best practices KW - lighting conditions KW - standard deviation KW - precision Y1 - 2024 SN - 978-84-09-59215-9 U6 - https://doi.org/10.21125/inted.2024.0802 SN - 2340-1079 SP - 2955 EP - 2961 PB - IATED Academy ER - TY - CHAP A1 - Ezer, Timur A1 - Grabinger, Lisa A1 - Hauser, Florian A1 - Staufer, Susanne A1 - Mottok, Jürgen T1 - EYE TRACKING METRICS FOR DISTINGUISHING GLOBAL AND FOCAL GAZE PATTERNS: A SYSTEMATIC LITERATURE REVIEW T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - Global and focal eye tracking gaze patterns are distinguished in a variety of domains, such as radiology research, empirical software engineering, behavioral psychology, and cartography research. A global gaze pattern is present if a participant in an eye tracking study gains an overview of the stimulus, whereas a focal pattern emerges during a more detailed evaluation of a specific part of the stimulus. With this higher-level measure of global and focal gaze patterns, cognitive effort, expertise levels, and even neurological characteristics - such as autism - can be quantified. Furthermore, with this measure, cognitive efforts of students in certain tasks can be investigated and clues for targeted support can be provided. These properties in particular make this eye tracking measure valuable for the education domain. In the field of eye tracking research, many researchers have established distinct criteria for differentiating global and focal gaze patterns. Moreover, it is rarely quantitatively measured which of these patterns is present, but rather determined based on qualitative considerations. However, some studies explicitly use quantitative metrics like saccade-length or fixation-duration to distinguish between global and focal gaze patterns. This is the focus of the present systematic literature review: It searches for and compiles the eye tracking metrics used in the literature to distinguish global from focal gaze patterns in a quantitative way. In doing so, this study fills the yawning gap in quantitative metrics for determining global and focal gaze patterns. In the long run, this can be used to answer questions about cognitive load and problems in processing tasks during eye tracking studies and to provide further insights into the cognitive processes of students. The present paper first discusses definitions of global and focal gaze patterns and presents examples in which this metric has already been applied. Then, the research questions together with search strings and search engines used for the systematic literature review are described. Finally, the results are summarized, presenting a compilation of and connections between quantitative metrics utilized in the literature to distinguish between global and focal viewing patterns. KW - Eye tracking KW - cognitive load KW - expertise KW - global KW - focal KW - ambient KW - local KW - metrics Y1 - 2024 SN - 978-84-09-59215-9 U6 - https://doi.org/10.21125/inted.2024.0814 SN - 2340-1079 SP - 3005 EP - 3014 PB - IATED Academy ER - TY - CHAP A1 - Ezer, Timur A1 - Greiner, Matthias A1 - Grabinger, Lisa A1 - Hauser, Florian A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Eye tracking al technology in education; data quality analysis and improvements T2 - Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023 N2 - Eye tracking has proven to be a powerful tool in a variety of empirical research areas; hence, it is steadily gaining attention. Driven by the expanding frontiers of Artificial Intelligence and its potential for data analysis, eye tracking technology offers promising applications in diverse fields, from usability research to cognitive research. The education sector in particular can benefit from the increased use of eye tracking technology - both indirectly, for example by studying the differences in gaze patterns between experts and novices to identify promising strategies, and directly by using the technology itself to teach in future classrooms. As with any empirical method, the results depend directly on the quality of the data collected. That raises the question of which parameters educators or researchers can influence to maximize the data quality of an eye tracker. This is the starting point of the present work: In an empirical study of eye tracking as an (educational) technology, we systematically examine factors that influence the data quality, such as illumination, sampling frequency, and head orientation - parameters that can be varied without much additional effort in everyday classroom or research use - using two human subjects, an artificial face, and the Tobii Pro Spectrum. We rely on metrics derived from the raw gaze data, such as accuracy or precision, to measure data quality. The obtained results derive practical advice for educators and researchers, such as using the lowest sampling frequency appropriate for a certain purpose. Thereby, this research fills a gap in the current understanding of eye tracker performance and, by offering best practices, enables researchers or teachers to produce data of the highest quality possible and therefore best results when using eye trackers in laboratories or future classrooms. Y1 - 2023 U6 - https://doi.org/10.21125/iceri.2023.1127 SP - 4500 EP - 4509 PB - IATED ER - TY - CHAP A1 - Homann, Alexander A1 - Grabinger, Lisa A1 - Hauser, Florian A1 - Mottok, Jürgen T1 - An Eye Tracking Study on MISRA C Coding Guidelines T2 - ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023 N2 - C is one of the most widely used programming languages - MISRA C is one of the most known sets of coding guidelines for C. This paper examines the usefulness and comprehensibility of the MISRA C:2012 guidelines in an eye tracking study. There, subjects encounter non-compliant code in four different code review settings: with no additional reference, with an actual MISRA C guideline, with a case-specific interpretation of a MISRA C guideline, and with a compliant version of the code. The data collected was analyzed not only in terms of the four presentation styles, but also by dividing the subjects into experience levels based on their semesters of study or years of work experience. Regarding the difference between actual and interpreted guidelines, we found that for interpreted guidelines the error detection rate is higher whereas the duration and frequency of visits to the guideline itself are mainly lower. This suggest that the actual guidelines are less useful and more difficult to understand. The former is contradicted by the subjects’ opinions: when surveyed, they rated the usefulness of the actual guidelines higher. Y1 - 2023 SN - 978-1-4503-9956-2 U6 - https://doi.org/10.1145/3593663.3593671 SP - 130 EP - 137 PB - ACM 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 - CHAP A1 - Bock, T. A1 - Mottok, Jürgen A1 - Köhler, Thorsten ED - Mottok, Jürgen ED - Ziemann, Olaf T1 - A gesture-based human-machine interface using stereoscopic depth images T2 - 2nd Applied Research Conference 2012 (ARC 2012), 25./26. June 2012, Nuremberg N2 - Reasonable integration of gesture-based automotive HMI-functionality offers potential safety benefits by reducing driver distractions and glance times to operate tertiary in-car devices. Stereo camera systems are a well investigated choice to perform the task of generating depth data for spatial gesture recognition. This paper describes the functionality of our stereo vision software, which is intended for application in a target system based on CMOS wafer-level cameras. The retrieved point cloud data was passed to a gesture-based sample application. Y1 - 2012 SP - 166 EP - 169 PB - Shaker CY - Aachen ER - TY - CHAP A1 - Maier, Robert A1 - Mottok, Jürgen ED - Trapp, Mario ED - Saglietti, Francesca ED - Spisländer, Marc ED - Bitsch, Friedemann T1 - BayesianSafety - an Open-Source Package for Causality-Guided, Multi-Model Safety Analysis T2 - Computer Safety, Reliability, and Security, 41st International Conference (SAFECOMP 2022): Munich, Germany, September 6–9, 2022, Proceedings T2 - Lecture notes in computer science ; 13414 N2 - Development and verification of modern, dependable automotive systems require appropriate modelling approaches. Classic automotive safety is described by the normative regulations ISO 26262, its relative ISO/PAS 21448, and their respective methodologies. In recent publications, an emerging demand to combine environmental influences, machine learning, or reasoning under uncertainty with standard-compliant analysis techniques can be noticed. Therefore, adapting established methods like FTA and proper tool support is necessary. We argue that Bayesian Networks (BNs) can be used as a central component to address and merge these demands. In this paper, we present our Open-Source Python package BayesianSafety. First, we review how BNs relate to data-driven methods, model-to-model transformations, and causal reasoning. Together with FTA and ETA, these models form the core functionality of our software. After describing currently implemented features and possibilities of combining individual modelling approaches, we provide an informal view of the tool’s architecture and of the resulting software ecosystem. By comparing selected publicly available safety and reliability analysis libraries, we outline that many relevant methodologies yield specialized implementations. Finally, we show that there is a demand for a flexible, unifying analysis tool that allows researching system safety by using multi-model and multi-domain approaches. KW - Package BayesianSafety KW - Causality KW - Bayesian Networks KW - Event Tree Analysis KW - Fault Tree Analysis Y1 - 2022 U6 - https://doi.org/10.1007/978-3-031-14835-4_2 SP - 17 EP - 30 PB - Springer Nature CY - Cham ER - TY - CHAP A1 - Maier, Robert A1 - Grabinger, Lisa A1 - Urlhart, David A1 - Mottok, Jürgen ED - Seguin, Christel ED - Zeller, Marc ED - Prosvirnova, Tatiana T1 - Towards Causal Model-Based Engineering in Automotive System Safety T2 - Model-Based Safety and Assessment, 8th International Symposium, IMBSA 2022: Munich, Germany, September 5–7, 2022, Proceedings N2 - Engineering is based on the understanding of causes and effects. Thus, causality should also guide the safety assessment of complex systems such as autonomous driving cars. To ensure the safety of the intended functionality of these systems, normative regulations like ISO 21448 recommend scenario-based testing. An important task here is to identify critical scenarios, so-called edge and corner cases. Data-driven approaches to this task (e.g. based on machine learning) cannot adequately address a constantly changing operational design domain. Model-based approaches offer a remedy – they allow including different sources of knowledge (e.g. data, human experts) into safety considerations. With this paper, we outline a novel approach for ensuring automotive system safety. We propose to use structural causal models as a probabilistic modelling language to combine knowledge about an open-context environment from different sources. Based on these models, we investigate parameter configurations that are candidates for critical scenarios. In this paper, we first discuss some aspects of scenario-based testing. We then provide an informal introduction to causal models and relate their development lifecycle to the established V-model. Finally, we outline a generic workflow for using causal models to identify critical scenarios and highlight some challenges that arise in the process. Y1 - 2022 U6 - https://doi.org/10.1007/978-3-031-15842-1_9 SP - 116 EP - 129 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Maier, Robert A1 - Grabinger, Lisa A1 - Urlhart, David A1 - Mottok, Jürgen T1 - Causal Models to Support Scenario-Based Testing of ADAS JF - IEEE Transactions on Intelligent Transportation Systems N2 - In modern vehicles, system complexity and technical capabilities are constantly growing. As a result, manufacturers and regulators are both increasingly challenged to ensure the reliability, safety, and intended behavior of these systems. With current methodologies, it is difficult to address the various interactions between vehicle components and environmental factors. However, model-based engineering offers a solution by allowing to abstract reality and enhancing communication among engineers and stakeholders. Applying this method requires a model format that is machine-processable, human-understandable, and mathematically sound. In addition, the model format needs to support probabilistic reasoning to account for incomplete data and knowledge about a problem domain. We propose structural causal models as a suitable framework for addressing these demands. In this article, we show how to combine data from different sources into an inferable causal model for an advanced driver-assistance system. We then consider the developed causal model for scenario-based testing to illustrate how a model-based approach can improve industrial system development processes. We conclude this paper by discussing the ongoing challenges to our approach and provide pointers for future work. KW - automated driving systems KW - Automation KW - Bayesian networks KW - Causal inference KW - Data models KW - ISO Standards KW - model-based testing KW - Safety KW - Task analysis KW - Testing KW - Vehicles Y1 - 2023 U6 - https://doi.org/10.1109/TITS.2023.3317475 SN - 1524-9050 SP - 1 EP - 17 PB - IEEE ER - TY - CHAP A1 - Maier, Robert A1 - Mottok, Jürgen T1 - Causality and Functional Safety - How Causal Models Relate to the Automotive Standards ISO 26262, ISO/PAS 21448, and UL 4600 T2 - 27th International Conference on Applied Electronics (AE): 06-07 September 2022, Pilsen, CZ N2 - With autonomous driving, the system complexity of vehicles will increase drastically. This requires new approaches to ensure system safety. Looking at standards like ISO 26262 or ISO/PAS 21448 and their suggested methodologies, an increasing trend in the recent literature can be noticed to incorporate uncertainty. Often this is done by using Bayesian Networks as a framework to enable probabilistic reasoning. These models can also be used to represent causal relationships. Many publications claim to model cause-effect relations, yet rarely give a formal introduction of the implications and resulting possibilities such an approach may have. This paper aims to link the domains of causal reasoning and automotive system safety by investigating relations between causal models and approaches like FMEA, FTA, or GSN. First, the famous “Ladder of Causation” and its implications on causality are reviewed. Next, we give an informal overview of common hazard and reliability analysis techniques and associate them with probabilistic models. Finally, we analyse a mixed-model methodology called Hybrid Causal Logic, extend its idea, and build the concept of a causal shell model of automotive system safety. KW - Causality KW - Reliability KW - Functional Safety Y1 - 2022 U6 - https://doi.org/10.1109/AE54730.2022.9920053 PB - IEEE ER - TY - CHAP A1 - Kristen, Meret A1 - Engl, Fabian A1 - Mottok, Jürgen T1 - Enhancing Phishing Detection: An Eye-Tracking Study on User Interaction and Oversights in Phishing Emails T2 - SECURWARE 2024 : The Eighteenth International Conference on Emerging Security Information, Systems and Technologies, November 03-07, 2024, Nice, France N2 - Phishing remains a significant threat to organizational security, necessitating effective countermeasures. This paper presents findings from an in-depth eye-tracking study with 103 participants, evaluating the effectiveness of phishing awareness tools and trainings. The study examines how a phishing awareness system influences user behavior, efficiency, and the ability to identify phishing attempts. By analyzing eye movements, the study reveals real-time interactions and oversights, providing insights into the decision-making process. Results indicate that while the system improves the efficiency of users already proficient in phishing detection, it does not universally enhance recognition rates. Notably, participants using the tool spent significantly less time looking at attachment-related phishing markers, indicating partial efficiency improvements. Since phishing attempts containing suspicious attachments were successful in 19% of cases, as compared to an overall phishing success rate of 15%, the phishing awareness tool is particularly useful here. A usability evaluation revealed that users reporting a higher perceived usability score profited more from the help of the tool. Additionally, no improvement in phishing detection rates was observed in users who had completed prior IT-security training, highlighting the necessity for a paradigm shift in phishing training to adequately prepare users for phishing attempts. Y1 - 2024 UR - https://www.thinkmind.org/library/SECURWARE/SECURWARE_2024/securware_2024_2_80_30041.html SN - 978-1-68558-206-7 SP - 71 EP - 80 PB - IARIA 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 - RPRT A1 - Taiber, Joachim A1 - Chowdury, M. A1 - Hammond, G. A1 - Hipp, V. A1 - Huttner, B. A1 - Lonien, J. A1 - Mottok, Jürgen A1 - Neukart, Florian A1 - Stengel, T. T1 - Unsettled Topics Concerning the Impact of Quantum Technologies on Automotive Cybersecurity N2 - Quantum computing is considered the “next big thing” when it comes to solving computational problems impossible to tackle using conventional computers. However, a major concern is that quantum computers could be used to crack current cryptographic schemes designed to withstand traditional cyberattacks. This threat also impacts future automated vehicles as they become embedded in a vehicle-to-everything (V2X) ecosystem. In this scenario, encrypted data is transmitted between a complex network of cloud-based data servers, vehicle-based data servers, and vehicle sensors and controllers. While the vehicle hardware ages, the software enabling V2X interactions will be updated multiple times. It is essential to make the V2X ecosystem quantum-safe through use of “post-quantum cryptography” as well other applicable quantum technologies. This SAE EDGE™ Research Report considers the following three areas to be unsettled questions in the V2X ecosystem: How soon will quantum computing pose a threat to connected and automated vehicle technologies? What steps and measures are needed to make a V2X ecosystem “quantum-safe?” What standardization is needed to ensure that quantum technologies do not pose an unacceptable risk from an automotive cybersecurity perspective? Y1 - 2020 U6 - https://doi.org/10.4271/EPR2020026 SN - 2640-3536 CY - Warrendale, Pennsylvania, USA ER - TY - CHAP A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Ezer, Timur A1 - Mottok, Jürgen A1 - Gruber, Hans ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Integrating deliberate practice in software engineering education T2 - ICERI 2024 Proceedings, 17th annual International Conference of Education, Research and Innovation,11-13 November, 2024, Seville, Spain Y1 - 2024 U6 - https://doi.org/10.21125/iceri.2024.1331 SP - 5457 EP - 5466 PB - IATED ER - TY - GEN A1 - Stark, T. A1 - Schreistetter, Stefan A1 - Reuter, Rebecca A1 - Hauser, Florian A1 - Holmqvist, Kenneth A1 - Mottok, Jürgen A1 - Gruber, Hans T1 - Learning from Gaze: Eye Movement Modeling Examples in Software Engineering Education T2 - Earli Book of Abstracts Y1 - 2021 UR - https://earli.org/assets/files/BOA-2021.pdf SP - 291 PB - Earli ER - TY - CHAP A1 - De, Sangita A1 - Niklas, Michael A1 - Brada, Premek A1 - Mottok, Jürgen T1 - Model Transformation of Application Software Component from Classic to Adaptive AUTOSAR: An Approach to Migrate Software Components T2 - SEAA 2018, the 44th EUROMICRO Conference on Software Engineering and Advanced Applications, August 29 - 31 2018, Prague, Czech Republic Y1 - 2018 SN - 978-3-902457-50-9 ER - TY - CHAP A1 - Bugert, Flemming A1 - Staufer, Susanne A1 - Bittner, Dominik A1 - Nadimpalli, Vamsi Krishna A1 - Ezer, Timur A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Mottok, Jürgen T1 - Ariadne's Thread for Unravelling Learning Paths: Identifying Learning Styles via Hidden Markov Models T2 - 2024 IEEE Global Engineering Education Conference (EDUCON), 08-11 May 2024, Kos Island, Greece N2 - Modern education through Learning Management Systems (LMSs) provides learners with personalized learning paths. This is achieved by first querying the learning style according to the theory of Felder and Silverman to recommend suitable learning content. However, a rigid learning style representation is lacking of adaptability to the learners' choices. Therefore, the present study evaluates the idea of providing adaption to the representation of learning styles by using Hidden Markov Models (HMMs). Thus, data is collected from participants out of the Higher Education Area. The Index of Learning Styles questionnaire is used to obtain the learning style based on the theory of Felder and Silverman. Also, a questionnaire that asks the respondents to create a preferred learning path with the sequence length of nine learning elements is provided. From the given data, we initially evaluate the probability relationships between learning styles and learning elements. Then, we use the Viterbi algorithm in HMMs to identify alterations in learning styles from the provided learning paths. The alignment is then quantified by introducing a metric called support value. The findings imply that our concept can be used to adapt the learning style based on the user's real choice of learning elements. Thus, the proposed model also offers a way to integrate a feedback loop within LMSs leading to an improvement of learning path recommendation algorithms. KW - Surveys KW - Knowledge engineering KW - Feedback loop KW - Learning management systems KW - Uncertainty KW - Viterbi algorithm Y1 - 2024 U6 - https://doi.org/10.1109/EDUCON60312.2024.10578825 SN - 2165-9567 SP - 1 EP - 7 PB - IEEE ER - TY - CHAP A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Mottok, Jürgen A1 - Jahn, Sabrina A1 - Nadimpalli, Vamsi Krishna T1 - The Expert’s View: Eye Movement Modeling Examples in Software Engineering Education T2 - Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023 N2 - This study investigates the impact of eye movement modeling examples in Software Engineering education. Software Engineering is a highly visual domain. The daily tasks of a software engineer (e.g., formulating requirements, creating UML diagrams, or conducting a code review) require in many cases the use of certain visual strategies. Although these strategies can be found for experts, it has been observed in different eye tracking studies that students have difficulties in learning and applying them. To familiarize students with these visual strategies and to provide them with a better understanding for the cognitive processes involved, a total of seven eye movement modeling examples was created. The seven eye movement modeling examples cover relevant parts of an introductory Software Engineering lecture; they are focused on typical situations in which visual strategies are applied. The results of a questionnaire-based evaluation shows that students consider the eye movement modeling examples as useful, feel supported in their learning process, and would like to see more use of them in the Software Engineering lecture. Furthermore, the students suggested that eye movement modeling examples should also be used in other lectures. Y1 - 2023 SN - 978-1-4503-9956-2 U6 - https://doi.org/10.1145/3593663.3593683 SP - 148 EP - 152 PB - ACM ER - TY - CHAP A1 - Bugert, Flemming A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Nadimpalli, Vamsi Krishna A1 - Staufer, Susanne A1 - Mottok, Jürgen T1 - Towards Learning Style Prediction based on Personality T2 - Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023 N2 - This paper assesses the relation between personality, demographics, and learning style. Hence, data is collected from 200 participants using 1) the BFI-10 to obtain the participant’s expression of personality traits according to the five-factor model, 2) the ILS to determine the participant’s learning style according to Felder and Silverman, and 3) a demographic questionnaire. From the obtained data, we train and evaluate a Bayesian network. Using Bayesian statistics, we show that age and gender slightly influence personality and that demographics as well as personality have at least a minor effect on learning styles. We also discuss the limitations and future work of the presented approach. Y1 - 2023 SN - 978-1-4503-9956-2 U6 - https://doi.org/10.1145/3593663.3593682 SP - 48 EP - 55 PB - ACM ER - TY - CHAP A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Nadimpalli, Vamsi Krishna A1 - Grabinger, Lisa A1 - Staufer, Susanne A1 - Mottok, Jürgen T1 - Towards Eye Tracking based Learning Style Identification T2 - Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023 N2 - The dropout rate at universities has been very high for years. Thereby, the inexperience and lack of knowledge of students in dealing with individual learning paths in various courses of study plays a decisive role. Adaptive learning management systems are suitable countermeasures, in which learners’ learning styles are classified using questionnaires or computationally intensive algorithms before a learning path is suggested accordingly. In this paper, a study design for student learning style classification using eye tracking is presented. Furthermore, qualitative and quantitative analyses clarify certain relationships between students’ eye movements and learning styles. With the help of classification based on eye tracking, the filling out of questionnaires or the integration of computationally or cost-intensive algorithms can be made redundant in the future. Y1 - 2023 SN - 978-1-4503-9956-2 U6 - https://doi.org/10.1145/3593663.3593680 SP - 138 EP - 147 PB - ACM ER - TY - CHAP A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Staufer, Susanne A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Towards personalized learning paths in adaptive learning management systems: bayesian modelling of psychological theories T2 - Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023 N2 - In educational research, non-personalized learning content increases learners' cognitive load, causing them to lower their performance and sometimes drop out of the course. Personalizing learning content with learners’ unique characteristics, like learning styles, personality traits, and learning strategies, is being suggested to improve learners’ success. Several theories exist for assessing learners’ unique characteristics. By the end of 2020, 71 learning style theories have been formulated, and research has shown that combining multiple learning style theories to recommend learning paths yields better results. As of the end of 2022, there is no single research that demonstrates a relationship between the Index of Learning Styles (ILS) based Felder-Silverman learning style model (FSLSM) dimensions, Big Five (BFI-10) based personality traits, and the Learning strategies in studying (LIST-K) based learning strategies factors for personalizing learning content. In this paper, an innovative approach is proposed to estimate the relationship between these theories and map the corresponding learning elements to create personalized learning paths. Respective questionnaires were distributed to 297 higher education students for data collection. A three-step approach was formulated to estimate the relationship between the models. First, a literature search was conducted to find existing studies. Then, an expert interview was carried out with a group of one software engineering education research professor, three doctoral students, and two master’s students. Finally, the correlations between the students' questionnaire responses were calculated. To achieve this, a Bayesian Network was built with expert knowledge from the three-step approach, and the weights were learned from collected data. The probability of individual FSLSM learning style dimensions was estimated for a new test sample. Based on the literature, the learning elements were mapped to the respective FSLSM learning style dimensions and were initiated as learning paths to the learners. The next steps are proposed to extend this framework and dynamically recommend learning paths in real time. In addition, the individual levels of learning style dimensions, personality traits, and learning strategies can be considered to improve the recommendations. Further, using probabilities for mapping learning elements to learning styles can increase the chance of initiating multiple learning paths for an individual learner. Y1 - 2023 U6 - https://doi.org/10.21125/iceri.2023.1144 SP - 4593 EP - 4603 PB - IATED ER - TY - CHAP A1 - Ezer, Timur A1 - Plößl, Moritz A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Staufer, Susanne A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Hauser, Florian A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Deep learning for eye movement classification T2 - ICERI 2024 Proceedings, 17th annual International Conference of Education, Research and Innovation,11-13 November, 2024, Seville, Spain Y1 - 2024 U6 - https://doi.org/10.21125/iceri.2024.1028 SP - 4056 EP - 4065 PB - IATED 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 - INPR A1 - Gaube, Susanne A1 - Jussupow, Ekaterina A1 - Kokje, Eesha A1 - Khan, Jowaria A1 - Bondi-Kelly, Elizabeth A1 - Schicho, Andreas A1 - Kitamura, Felipe Campos A1 - Koch, Timo Kevin A1 - Ezer, Timur A1 - Mottok, Jürgen A1 - Lermer, Eva A1 - Ghassemi, Marzyeh A1 - Colak, Errol T1 - Underreliance Harms Human-AI Collaboration More Than Overreliance in Medical Imaging N2 - Importance: The use of artificial intelligence (AI) to support clinicians in diagnostic decision-making holds significant potential; however, evidence regarding its clinical utility remains mixed. In many cases, the interaction between healthcare professionals and AI systems does not improve collaborative performance compared to the standalone performance of humans or AI. Currently, the underlying mechanisms that limit human-AI collaboration are poorly understood. Objective: To examine the impact of AI advice on diagnostic decision-making among experts and novices, focusing on understanding the role of explainability (XAI) on users’ reliance on advice. Design, Setting, and Participants: A mixed-methods design combining a crossover experimental design with a think-aloud and an eye-tracking study arm was conducted in 2023. Participants were task experts (radiologists) and novices (non-radiologist physicians and medical trainees) from 10 countries, with the think-aloud and eye-tracking conducted in Germany. Intervention: Participants reviewed 50 patient cases containing head CT scans and patient information. Every case was reviewed in three time-separate sessions in randomized order. In each session, participants were exposed to a different experimental condition: (a) control, i.e., no AI prediction presented; (b) basic advice, i.e., AI prediction without annotations; and (c) XAI advice, i.e., AI prediction with annotations. For each case, participants had to determine if the patients had an intracranial hemorrhage (ICH), rate their confidence, and, if applicable, the usefulness of the AI advice. Main Outcome(s) and Measure(s): Diagnostic performance, confidence in the diagnosis, case reading time, and AI advice usefulness ratings. Results: The data analysis included 125 participants. The mean age was 28.5 years (SD = 6.72), and 55.2% identified as female. Underreliance on correct AI advice was associated with high uncertainty and had a more detrimental impact on diagnostic performance than overreliance on incorrect advice. XAI advice reduced underreliance and improved performance and confidence, particularly when reviewing more difficult cases with ICH. AI advice, particularly XAI, did not reduce reading time. XAI was perceived as more useful than basic AI advice, especially among novices. Conclusions and Relevance: Our findings indicate that underreliance on AI might be more harmful than overreliance, highlighting the need to develop efficient counterstrategies beyond current XAI methods. Y1 - 2024 U6 - https://doi.org/10.31219/osf.io/4wv8j PB - OSFPreprints ER - TY - CHAP A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Engl, Fabian A1 - Mottok, Jürgen ED - Mottok, Jürgen ED - Hagel, Georg T1 - Eye Movement Modelling Examples on Usability Heuristics T2 - Proceedings of the 6th European Conference on Software Engineering Education : ECSEE 2025, Seeon Germany, June 02-04, 2025 N2 - The user interface (UI) and user experience (UX) design is of crucial importance for human-computer interaction (HCI), particularly in the context of web applications. In light of the high expectations of users and the competitive nature of the market, it is imperative to employ usability measurement techniques to avoid losing users. Heuristic evaluation (HE) is a cost- and resource-efficient method for evaluating the usability of websites in which evaluators are guided by heuristics. However, the level of expertise of the evaluators has a significant impact on the results, with experts identifying up to 50% more usability issues than novices. To address this gap, this paper proposes Eye Movement Modeling Examples (EMMEs) to demonstrate Jakob Nielsen’s ten usability heuristics in an easy-to-understand format for all levels of experience while also incorporating expert knowledge. In particular, the eye movements and verbal feedback of a usability expert are recorded as the expert analyses the usability of a simple website application in terms of Jakob Nielsen’s ten usability heuristics. This reveals the strategies and cognitive processes of the expert when assessing the usability of a website and makes them more tangible for non-experts or novices. The findings of a questionnaire-based assessment indicate that EMMEs are perceived as beneficial and supportive during the learning process. Ultimately, this comprehensive analysis not only enables a deeper understanding of heuristics for usability novices, but could also lead to EMMEs being applied more efficiently in diverse domains. Y1 - 2025 SN - 9798400712821 U6 - https://doi.org/10.1145/3723010.3723035 SP - 106 EP - 114 PB - ACM 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 - Hauser, Florian A1 - Staufer, Susanne A1 - Grabinger, Lisa A1 - Röhrl, Simon A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - On the analysis of student learning strategies: using the LIST-K questionnaire ro generate ai-based individualized learning paths T2 - Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023 N2 - This paper presents the results of a data collection with the LIST-K questionnaire. This questionnaire measures students’ learning strategies and shows which strategies are particularly dominant or rather weak. Learning strategies have long been a major area of research in educational science and psychology. In these disciplines, learning strategies are understood as intentional behaviors and cognitive skills that learners employ to effectively complete learning tasks, by selecting, acquiring, organizing, and integrating information into their existing knowledge for long-term retention. The LIST-K, developed by Klingsieck in 2018, was chosen for accessing learning strategies due to its thematic suitability, widespread use, and test economy. It covers a total of four main categories (i.e., cognitive strategies, metacognitive strategies, management of internal resources, and management of external resources), each of which are subdivided into further subscales. With a total of 39 items answered via a 5-step Likert scale, the LIST-K can cover the topic relatively comprehensively and at the same time be completed in a reasonable amount of time of approximately 10 minutes. The LIST-K was used as part of a combined data collection along with other questionnaires on their personal data, their preferences regarding certain learning elements, their learning style (i.e. the ILS), and personality (i.e. the BFI-10). A total of 207 students from different study programs participated via an online survey created using the survey tool "LimeSurvey". Participation in the study was voluntary, anonymously, and in compliance with the GDPR. Overall, the results of the LIST-K show that students are willing to work intensively on relevant topics intensively and to perform beyond the requirements of the course seeking additional learning material. At the same time, however, it is apparent that the organization of their own learning process could still be improved. For example, students start repeating content too late (mean=2.70; SD=0.92) and do not set goals for themselves and do not create a learning plan (mean=3.19; SD=0.90). They also learn without a schedule (mean=2.23; SD=0.97) and miss opportunities to learn together with other students (mean=3.17; SD=0.94). The findings of the data collection will be used to create an AI-based adaptive learning management system that will create individualized learning paths for students in their respective courses. From the results of the LIST-K, it appears that the adaptive learning management system should primarily support organizational aspects of student learning. Even small impulses (an individual schedule of when to learn what or a hierarchical structuring of the learning material) could help students to complete their courses more successfully and improve their learning. Y1 - 2023 U6 - https://doi.org/10.21125/iceri.2023.1147 SP - 4611 EP - 4620 PB - IATED ER - TY - CHAP A1 - Bugert, Flemming A1 - Nadimpalli, Vamsi Krishna A1 - Bittner, Dominik A1 - Ezer, Timur A1 - Grabinger, Lisa A1 - Maier, Robert A1 - Röhrl, Simon A1 - Staufer, Susanne A1 - Hauser, Florian A1 - Mottok, Jürgen ED - Mottok, Jürgen ED - Hagel, Georg T1 - ML based Evaluation Methodology for Learning Path Recommender Systems T2 - Proceedings of the 6th European Conference on Software Engineering Education : ECSEE 2025, Seeon Germany, June 02-04, 2025 N2 - In education, recommender systems can provide students with personalized learning materials based on their preferences. When comparing various recommendation algorithms, the main question is, which algorithm provides the most suitable recommendations for each student. Answering this question requires a quantitative evaluation methodology (i.e. a concrete metric) for ranking the results of (even non-deterministic) recommender systems. While there is already literature on this topic, the uniqueness of our approach lies in the application of machine learning: we deploy a likelihood based analysis via Hidden Markov Models named Aiakos. With this strategy, we aim to provide data-driven insights about accuracy and stability of recommendations towards a more reasonable selection of the appropriate recommender system. The training data for the Hidden Markov Models is collected from 80 students. Data from another 26 students is then used to discuss the behavior of our evaluation procedure considering a single recommendation as well as the results from 100 recommendations. Furthermore, the proposed concept allows to be applied to other domains as well. Y1 - 2025 SN - 9798400712821 U6 - https://doi.org/10.1145/3723010.3723022 SP - 40 EP - 48 PB - ACM ER - TY - CHAP A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Bittner, Dominik A1 - Staufer, Susanne A1 - Röhrl, Simon A1 - Hauser, Florian A1 - Ezer, Timur A1 - Grabinger, Lisa A1 - Maier, Robert A1 - Mottok, Jürgen T1 - Probabilistic Machine Learning for Simulating Complex Learner Profiles T2 - 2024 21st International Conference on Information Technology Based Higher Education and Training (ITHET), 06-08 November 2024, Paris, France N2 - Data is the foundation of all machine learning applications. In education science, especially for the learner characteristics that drive personalized learning, it is difficult to collect and often uncertain. It is challenging to model, train, evaluate, and analyze the underlying algorithms when developing AI-based systems and having small sample sizes. To address these problems, we present a synthetic data generator utilising probabilistic models. This generator can effectively model and simulate complex learner profiles. To achieve this, we collected extensive data on learning styles, learning strategies, personalities, and preferred learning paths from 593 students over several semesters at a higher education level. Then, Bayesian networks, Hidden Markov Models, and Markov Chains are used to model the relationships between learner profiles. Using the Bayesian information criterion, and cross-validation with log-likelihood scores, we compare various models to select the best fitting one for synthesizing the data. The synthetic data is then evaluated using statistical validation techniques. In addition, we developed a simulation module with the option to simulate learner profiles based on manual user-defined inputs. The data and code used in this work are available as open source1110.5281/zenodo.13768136 [Titel anhand dieser DOI in Citavi-Projekt übernehmen] contributing to open science and developers for customized simulated data. In the future, this data will refine the training, evaluation, analysis, and benchmarking of algorithms for personalized learning. KW - probabilistic models KW - synthetic data KW - learner characteristics KW - generative AI KW - higher education area Y1 - 2024 SN - 979-8-3315-1663-5 U6 - https://doi.org/10.1109/ITHET61869.2024.10837641 SN - 2473-2060 SP - 1 EP - 10 PB - IEEE ER - TY - CHAP A1 - Nadimpalli, Vamsi Krishna A1 - Staufer, Susanne A1 - Ezer, Timur A1 - Bugert, Flemming A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Röhrl, Simon A1 - Maier, Robert A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Predicting learner characteristics using machine learning T2 - ICERI 2024 Proceedings, 17th annual International Conference of Education, Research and Innovation,11-13 November, 2024, Seville, Spain N2 - In education science research, data collection is challenging due to difficulty identifying students at the higher education level, privacy concerns, and varying levels of student engagement. Importantly, psychological questionnaires can be lengthy, leading to incomplete responses. We conducted repeated studies, and over time, the focus of the research adapted, introducing new materials and consequently leading to missing learner characteristics in some datasets. In this research, the issue of incomplete learner characteristics is addressed using data from three different studies: winter term 2022/2023 (n=297), summer term 2023 (n=274), and winter term 2023/2024 (n=25). These studies collected various learner characteristics, such as learning styles, personalities, learning strategies, and learning element preferences. However, learning element preferences and learning strategies were missing in the winter term of 2022, and the summer term of 2023 respectively. To analyze the data and predict these missing features, statistical analysis, and machine learning techniques were employed. Then, these models are rigorously evaluated using cross-validation and performance metrics like accuracy, precision, recall, and F1-score. Our findings provide insights into the relationships between learners' learning styles, personalities, learning strategies, and learning element preferences. This offers valuable implications for the design and implementation of educational interventions, like learning path recommendations. The results imply that machine learning models can predict missing learner characteristics, thus addressing the problem of incomplete data in educational research Y1 - 2024 U6 - https://doi.org/10.21125/iceri.2024.1454 SP - 6005 EP - 6014 PB - IATED ER - TY - CHAP A1 - Hammer, Pascal A1 - Mottok, Jürgen T1 - Prototyping for high-performance random number generators for critical systems T2 - 2025 International Conference on Applied Electronics (AE), 08-09. September 2025, Pilsen Czech Republic N2 - The security of modern cryptographic applications depends on the quality of their random number generators (RNGs). While physical true random number generators (PTRNGs) provide high-quality randomness, their performance is often insufficient for high-throughput applications. On the other hand, deterministic random number generators (DRNGs) offer better speed but lack true randomness. This paper presents an approach to developing a high-performance PTRNG. The research focuses on optimizing the digitization of analog noise signals. For this purpose, an ADC was selected that can digitize analog signals at a high clock rate. The functionality of the ADC could be verified by digitizing reference signals. Preliminary results by digitizing the analog noise signal demonstrates the feasibility of the proposed approach, but highlight challenges in achieving good results for Min-Entropy. Y1 - 2025 U6 - https://doi.org/10.1109/AE66163.2025.11197780 PB - IEEE 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 -