@inproceedings{BittnerHendricksHornetal., author = {Bittner, Dominik and Hendricks, Ricky-Ricardo and Horn, Luca and Mottok, J{\"u}rgen}, title = {In-depth Benchmarking of Transfer Learning Techniques for Improved Bottle Recognition}, series = {2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS), Guayaquil, Ecuador, 04-07 July 2023}, booktitle = {2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS), Guayaquil, Ecuador, 04-07 July 2023}, publisher = {IEEE}, isbn = {979-8-3503-3337-4}, doi = {10.1109/ICPRS58416.2023.10178995}, pages = {1 -- 6}, abstract = {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.}, language = {en} } @inproceedings{RoehrlStauferNadimpallietal., author = {R{\"o}hrl, Simon and Staufer, Susanne and Nadimpalli, Vamsi Krishna and Bugert, Flemming and Bugert, Flemming and Hauser, Florian and Grabinger, Lisa and Bittner, Dominik and Ezer, Timur and Mottok, J{\"u}rgen}, title = {PYTHIA - AI SUGGESTED INDIVIDUAL LEARNING PATHS FOR EVERY STUDENT}, series = {INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024}, booktitle = {INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024}, isbn = {978-84-09-59215-9}, issn = {2340-1079}, doi = {10.21125/inted.2024.0783}, pages = {2871 -- 2880}, abstract = {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.}, language = {en} } @article{FuxenSchoenhaerlSchmidtetal., author = {Fuxen, Philipp and Sch{\"o}nh{\"a}rl, Stefan and Schmidt, Jonas and Gerstner, Mathias and Jahn, Sabrina and Graf, Julian and Hackenberg, Rudolf and Mottok, J{\"u}rgen}, title = {A Cybersecurity Education Platform for Automotive Penetration Testing}, series = {International Journal On Advances in Security}, volume = {15}, journal = {International Journal On Advances in Security}, number = {3\&4}, publisher = {IARIA}, issn = {1942-2636}, pages = {106 -- 118}, abstract = {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.}, language = {en} } @inproceedings{StauferHauserGrabingeretal., author = {Staufer, Susanne and Hauser, Florian and Grabinger, Lisa and Bittner, Dominik and Nadimpalli, Vamsi Krishna and Bugert, Flemming and Ezer, Timur and R{\"o}hrl, Simon and Mottok, J{\"u}rgen}, title = {Learning elements in LMS - a survey among students}, series = {INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024}, booktitle = {INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024}, publisher = {IATED}, isbn = {978-84-09-59215-9}, issn = {2340-1079}, doi = {10.21125/inted.2024.1087}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-71135}, pages = {4224 -- 4231}, abstract = {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.}, language = {en} } @inproceedings{GrabingerEzerHauseretal., author = {Grabinger, Lisa and Ezer, Timur and Hauser, Florian and Mottok, J{\"u}rgen}, title = {The impact of eyenalyzer}, series = {ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain}, booktitle = {ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain}, publisher = {IATED}, isbn = {978-84-09-63010-3}, issn = {2340-1095}, doi = {10.21125/iceri.2024.0271}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-78215}, pages = {695 -- 701}, abstract = {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.}, language = {en} } @inproceedings{JahnWeissAkcakocaetal., author = {Jahn, Sabrina and Weiss, Nils and Akcakoca, Ugur and Mottok, J{\"u}rgen}, title = {Under The Hood - A Concept for Virtualized Automotive Security Education}, series = {EDULEARN21: Proceedings, 13th International Conference on Education and New Learning Technologies, Online Conference. 5-6 July, 2021}, booktitle = {EDULEARN21: Proceedings, 13th International Conference on Education and New Learning Technologies, Online Conference. 5-6 July, 2021}, editor = {G{\´o}mez Chova, Luis and L{\´o}pez Mart{\´i}nez, A. and Candel Torres, I.}, isbn = {978-84-09-31267-2}, issn = {2340-1117}, doi = {10.21125/edulearn.2021.1231}, pages = {6109 -- 6118}, abstract = {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.}, language = {en} } @inproceedings{EzerGrabingerHauseretal., author = {Ezer, Timur and Grabinger, Lisa and Hauser, Florian and Staufer, Susanne and Mottok, J{\"u}rgen}, title = {EYE TRACKING AS TECHNOLOGY IN EDUCATION: FURTHER INVESTIGATION OF DATA QUALITY AND IMPROVEMENTS}, series = {INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024}, booktitle = {INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024}, publisher = {IATED Academy}, isbn = {978-84-09-59215-9}, issn = {2340-1079}, doi = {10.21125/inted.2024.0802}, pages = {2955 -- 2961}, abstract = {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.}, language = {en} } @inproceedings{EzerGrabingerHauseretal., author = {Ezer, Timur and Grabinger, Lisa and Hauser, Florian and Staufer, Susanne and Mottok, J{\"u}rgen}, title = {EYE TRACKING METRICS FOR DISTINGUISHING GLOBAL AND FOCAL GAZE PATTERNS: A SYSTEMATIC LITERATURE REVIEW}, series = {INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024}, booktitle = {INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024}, publisher = {IATED Academy}, isbn = {978-84-09-59215-9}, issn = {2340-1079}, doi = {10.21125/inted.2024.0814}, pages = {3005 -- 3014}, abstract = {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.}, language = {en} } @inproceedings{EzerGreinerGrabingeretal., author = {Ezer, Timur and Greiner, Matthias and Grabinger, Lisa and Hauser, Florian and Mottok, J{\"u}rgen}, title = {Eye tracking al technology in education; data quality analysis and improvements}, series = {Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023}, booktitle = {Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023}, editor = {G{\´o}mez Chova, Luis and Gonz{\´a}lez Mart{\´i}nez, Chelo and Lees, Joanna}, publisher = {IATED}, doi = {10.21125/iceri.2023.1127}, pages = {4500 -- 4509}, abstract = {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.}, language = {en} } @inproceedings{HomannGrabingerHauseretal., author = {Homann, Alexander and Grabinger, Lisa and Hauser, Florian and Mottok, J{\"u}rgen}, title = {An Eye Tracking Study on MISRA C Coding Guidelines}, series = {ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023}, booktitle = {ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023}, publisher = {ACM}, isbn = {978-1-4503-9956-2}, doi = {10.1145/3593663.3593671}, pages = {130 -- 137}, abstract = {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.}, language = {en} } @inproceedings{BockMottokKoehler, author = {Bock, T. and Mottok, J{\"u}rgen and K{\"o}hler, Thorsten}, title = {A gesture-based human-machine interface using stereoscopic depth images}, series = {2nd Applied Research Conference 2012 (ARC 2012), 25./26. June 2012, Nuremberg}, booktitle = {2nd Applied Research Conference 2012 (ARC 2012), 25./26. June 2012, Nuremberg}, editor = {Mottok, J{\"u}rgen and Ziemann, Olaf}, publisher = {Shaker}, address = {Aachen}, pages = {166 -- 169}, abstract = {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.}, language = {en} } @inproceedings{MaierMottok, author = {Maier, Robert and Mottok, J{\"u}rgen}, title = {BayesianSafety - an Open-Source Package for Causality-Guided, Multi-Model Safety Analysis}, series = {Computer Safety, Reliability, and Security, 41st International Conference (SAFECOMP 2022): Munich, Germany, September 6-9, 2022, Proceedings}, booktitle = {Computer Safety, Reliability, and Security, 41st International Conference (SAFECOMP 2022): Munich, Germany, September 6-9, 2022, Proceedings}, editor = {Trapp, Mario and Saglietti, Francesca and Spisl{\"a}nder, Marc and Bitsch, Friedemann}, publisher = {Springer Nature}, address = {Cham}, doi = {10.1007/978-3-031-14835-4_2}, pages = {17 -- 30}, abstract = {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.}, language = {en} } @inproceedings{MaierGrabingerUrlhartetal., author = {Maier, Robert and Grabinger, Lisa and Urlhart, David and Mottok, J{\"u}rgen}, title = {Towards Causal Model-Based Engineering in Automotive System Safety}, series = {Model-Based Safety and Assessment, 8th International Symposium, IMBSA 2022: Munich, Germany, September 5-7, 2022, Proceedings}, booktitle = {Model-Based Safety and Assessment, 8th International Symposium, IMBSA 2022: Munich, Germany, September 5-7, 2022, Proceedings}, editor = {Seguin, Christel and Zeller, Marc and Prosvirnova, Tatiana}, publisher = {Springer Nature}, address = {Cham}, doi = {10.1007/978-3-031-15842-1_9}, pages = {116 -- 129}, abstract = {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.}, language = {en} } @article{MaierGrabingerUrlhartetal., author = {Maier, Robert and Grabinger, Lisa and Urlhart, David and Mottok, J{\"u}rgen}, title = {Causal Models to Support Scenario-Based Testing of ADAS}, series = {IEEE Transactions on Intelligent Transportation Systems}, journal = {IEEE Transactions on Intelligent Transportation Systems}, publisher = {IEEE}, issn = {1524-9050}, doi = {10.1109/TITS.2023.3317475}, pages = {1 -- 17}, abstract = {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.}, language = {en} } @inproceedings{MaierMottok, author = {Maier, Robert and Mottok, J{\"u}rgen}, title = {Causality and Functional Safety - How Causal Models Relate to the Automotive Standards ISO 26262, ISO/PAS 21448, and UL 4600}, series = {27th International Conference on Applied Electronics (AE): 06-07 September 2022, Pilsen, CZ}, booktitle = {27th International Conference on Applied Electronics (AE): 06-07 September 2022, Pilsen, CZ}, publisher = {IEEE}, doi = {10.1109/AE54730.2022.9920053}, pages = {6}, abstract = {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.}, language = {en} } @inproceedings{KristenEnglMottok, author = {Kristen, Meret and Engl, Fabian and Mottok, J{\"u}rgen}, title = {Enhancing Phishing Detection: An Eye-Tracking Study on User Interaction and Oversights in Phishing Emails}, series = {SECURWARE 2024 : The Eighteenth International Conference on Emerging Security Information, Systems and Technologies, November 03-07, 2024, Nice, France}, booktitle = {SECURWARE 2024 : The Eighteenth International Conference on Emerging Security Information, Systems and Technologies, November 03-07, 2024, Nice, France}, publisher = {IARIA}, isbn = {978-1-68558-206-7}, pages = {71 -- 80}, abstract = {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.}, language = {en} } @inproceedings{StauferHauserGrabingeretal., author = {Staufer, Susanne and Hauser, Florian and Grabinger, Lisa and Bittner, Dominik and Nadimpalli, Vamsi Krishna and Mottok, J{\"u}rgen}, title = {Learning elements in online learning management systems}, series = {Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023}, booktitle = {Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023}, editor = {G{\´o}mez Chova, Luis and Gonz{\´a}lez Mart{\´i}nez, Chelo and Lees, Joanna}, publisher = {IATED}, doi = {10.21125/iceri.2023.0815}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-67725}, pages = {3121 -- 3130}, language = {en} } @inproceedings{StauferNadimpalliHauseretal., author = {Staufer, Susanne and Nadimpalli, Vamsi Krishna and Hauser, Florian and Bittner, Dominik and Grabinger, Lisa and Bugert, Flemming and Ezer, Timur and R{\"o}hrl, Simon and Mottok, J{\"u}rgen}, title = {Persistence of Questionnaire Data on Learning Styles, Learning Strategies AND Personality Traits}, series = {ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain}, booktitle = {ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain}, publisher = {IATED}, isbn = {978-84-09-63010-3}, issn = {2340-1095}, doi = {10.21125/iceri.2024.1524}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-78246}, pages = {6310 -- 6319}, abstract = {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.}, language = {en} } @article{RoehrlStauferBugertetal., author = {R{\"o}hrl, Simon and Staufer, Susanne and Bugert, Flemming and Nadimpalli, Vamsi Krishna and Hauser, Florian and Grabinger, Lisa and Bittner, Dominik and Ezer, Timur and Altweck, Ricardo and Graf, Sabine and Kriza, Thomas and Mottok, J{\"u}rgen}, title = {Ethical Considerations of AI in Education: A Case Study based on Pythia Learning Enhancement System}, series = {IEEE Access}, volume = {11}, journal = {IEEE Access}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, issn = {2169-3536}, doi = {10.1109/ACCESS.2025.3583975}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-83403}, pages = {1 -- 25}, abstract = {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.}, language = {en} } @techreport{TaiberChowduryHammondetal., author = {Taiber, Joachim and Chowdury, M. and Hammond, G. and Hipp, V. and Huttner, B. and Lonien, J. and Mottok, J{\"u}rgen and Neukart, Florian and Stengel, T.}, title = {Unsettled Topics Concerning the Impact of Quantum Technologies on Automotive Cybersecurity}, address = {Warrendale, Pennsylvania, USA}, issn = {2640-3536}, doi = {10.4271/EPR2020026}, abstract = {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?}, language = {en} }