Johannes SchleissOtto-von-Guericke-Universität Magdeburg | OvGU · Institute of Intelligent Cooperating Systems (ICS)
Johannes Schleiss
Master of Science
Creating the future of education.
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28
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Publications (28)
The use of Artificial Intelligence (AI) in engineering is on the rise and comes with the promise of cost reductions and efficiency gains. However, classical engineers often lack the necessary skills to implement data-driven solutions. At the same time, computer scientists lack the required understanding of engineering systems. Thus, we need to exte...
A major challenge in engineering education is to empower students to use their acquired technical skills to solve real-world problems. In particular, methods of Artificial Intelligence (AI) need to be studied as tools in their respective application contexts. This puts pressure on university lecturers concerning the didactical design and elaboratio...
The use of artificial intelligence (AI) is becoming increasingly important in various domains, making education about AI a necessity. The interdisciplinary nature of AI and the relevance of AI in various fields require that university instructors and course developers integrate AI topics into the classroom and create so-called domain-specific AI co...
Die voranschreitende Digitalisierung und insbesondere der Einsatz von Künstlicher Intelligenz (KI) in der Bildung eröffnen neue Möglichkeiten des Lernens. Bildung kann stärker individuell sowie zeitlich und räumlich entgrenzt stattfinden. ChatGPT verdeutlicht, wie dynamisch die Entwicklungen im Bereich KI sind. Das in Zunahme begriffene Interesse a...
In this research paper we examine undergraduate students' use of and perceptions of generative AI (GenAI). Students are early adopters of the technology, utilizing it in atypical ways and forming a range of perceptions and aspirations about it. To understand where and how students are using these tools and how they view them, we present findings fr...
Die wachsende Bedeutung von Data Literacy sowie Kompetenzen im Umgang mit Künstlicher Intelligenz (KI) spiegelt sich zunehmend auch im Bildungswesen wider. Dies führt zu einem wachsenden Bedarf an Aus-und Weiterbildung über KI. Bislang mangelt es dabei noch an koordinierten Herangehensweisen und einem strukturierten Austausch, um Ergebnisse verschi...
Building up competencies in working with data and tools of Artificial Intelligence (AI) is becoming more relevant across disciplinary engineering fields. While the adoption of tools for teaching and learning, such as ChatGPT, is garnering significant attention, integration of AI knowledge, competencies, and skills within engineering education is la...
In this practice paper, we propose a framework for integrating AI into disciplinary engineering courses and curricula. The use of AI within engineering is an emerging but growing area and the knowledge, skills, and abilities (KSAs) associated with it are novel and dynamic. This makes it challenging for faculty who are looking to incorporate AI with...
Dieses Papier richtet sich an Bildungs- und Digitalpolitiker*innen aus Bund und Ländern, die sich für die Förderung offener und gemeinwohlorientierter KI in der Bildungspraxis einsetzen möchten. Es richtet sich an Personen, die KI-Anwendungen in der Bildung fördern möchten, die zum einen auf offenen Trainingsdaten und Modellen beruhen und die zum a...
Der Beitrag untersucht Auswirkungen und Fragestellungen von generativen Sprachmo-dellen, einer Form der Künstlichen Intelligenz (KI), in den Bereichen von Kompetenzen, Prüfungen und Lehr-Lern-Szenarien. Wir diskutieren, inwiefern KI neue Kompetenzen er-fordert, Kompetenzen an Relevanz verlieren und Kompetenzen verloren gehen. Die teil-weise verände...
Higher education institutions (HEIs) must navigate diverse stakeholder interests and align their efforts towards a common goal to sustainably fulfill their missions. Co-creating visions is a promising approach to developing shared visions and thus aligning stakeholders’ interests. However, there is a lack of methodological guidance to support indiv...
Data and AI literacy is an important enabler for informed decision making in the data age. To inform educational programs and policies, it is important to create a common understanding about the required knowledge and skills. In this paper, we propose a novel taxonomy to data and AI literacy based on qualitative literature analysis and expert group...
Im Wintersemester 2023/2024 wird in Sachsen-Anhalt der Kooperationsstudiengang »AI Engineering-Künstliche Intelligenz in den Ingenieurwissenschaften« eingeführt. Ziel des Studiengangs ist es, Fachkräfte in der Entwicklung und Implementierung industrieller KI-Lösungen auszubilden. Im ersten Fachsemester absolvieren die Studierenden das Modul »Einfüh...
A growing number of courses seek to increase the basic artificial-intelligence skills (“AI literacy”) of their participants. At this time, there is no valid and reliable measurement tool that can be used to assess AI-learning gains. However, the existence of such a tool would be important to enable quality assurance and comparability. In this study...
As Artificial Intelligence (AI) becomes increasingly important in engineering, instructors need to incorporate AI concepts into their subject-specific courses. However, many teachers may lack the expertise to do so effectively or don't know where to start. To address this challenge, we have developed the AI Course Design Planning Framework to help...
The integration of tools and methods of Artificial Intelligence (AI) into the engineering domain has become increasingly important, and with it comes a shift in required competencies. As a result, engineering education should now incorporate competencies into its courses and curricula. While interdisciplinary education at a subject level has alread...
Grounding the design of educational interventions and their analysis in theory allows us to understand and interpret results of interventions and advance educational theories. Moreover, building an understanding of which educational theories are used and how they are used can build a consensus among researchers and mature the research in a field. I...
The use of predictive models in education promises individual support and personalization for students. To develop trustworthy models, we need to understand what factors and causes contribute to a prediction. Thus, it is necessary to develop models that are not only accurate but also explainable. Moreover, we need to conduct holistic model evaluati...
Die voranschreitende Digitalisierung und insbesondere der Einsatz von Künstlicher Intelligenz (KI) in der Bildung eröffnen neue Möglichkeiten des Lernens. Bildung kann stärker individuell sowie zeitlich und räumlich entgrenzt stattfinden. ChatGPT verdeutlicht, wie dynamisch die Entwicklungen im Bereich KI sind. Das in Zunahme begriffene Interesse a...
Der zweite Fellow-Jahrgang des KI-Campus teilt in einem neuen Sammelband seine Erfahrungen mit der Integration digitaler Lernangebote zum Thema Künstliche Intelligenz (KI) in die Hochschullehre. Der Fokus liegt dabei auf der Anwendungsorientierung. Zehn Beiträge zeigen das breite Spektrum an Einsatzmöglichkeiten der offen lizenzierten und frei verf...
Educational Technology (EdTech) Angeboten, die auf Künstlicher Intelligenz (KI) basieren, werden aktuell große Chancen für die Umsetzung adaptiver und individueller Lernszenarien zugeschrieben. Jedoch führen fehlendes Wissen und Ängste im Umgang mit KI zu einer Verunsicherung, die den Einsatz erschwert oder sogar verhindert und damit Chancen für Le...
The rise of Artificial Intelligence in Education opens up new possibilities for analysis of student data. However, the protection of private data in these applications is a major challenge. According to data regulations, the application designer is responsible for technical and organizational measures to ensure privacy. This paper aims to guide dev...
Humans efficiently extract relevant information from complex auditory stimuli. Oftentimes, the interpretation of the signal is ambiguous and musical meaning is derived from the subjective context. Predictive processing interpretations of brain function describe subjective music experience driven by hierarchical precision-weighted expectations. Ther...
Active Inference states that the human brain minimizes a statistical quantity of surprise with respect to
current observations and the planned future [1]. So far, implementations based on active inference with artificial
neural networks have been used to model individual planners and interaction between multiple autonomous
agents [2]. However, the...
Humans efficiently extract relevant information from complex auditory stimuli. Oftentimes, the interpretation of the signal is ambiguous and musical meaning is derived from the subjective context. Predictive processing interpretations of brain function describe subjective music experience driven by hierarchical precision-weighted expectations. Ther...
Conceptual knowledge about objects is essential for humans, as well as for animals, to interact with their environment. On this basis, the objects can be understood as tools, a selection process can be implemented and their usage can be planned in order to achieve a specific goal. The conceptual knowledge, in this case, is primarily concerned about...
Cooperative Systems promise increased performance by enriching environmental perception through shared data. Conversely, the entailed openness of the individual system architectures threatens their safety. Recent works focus on a run-time safety assessment to address this threat and thereby aim for high abstractions to provide general interfaces. O...
Tool-use applications in robotics require conceptual knowledge about objects for informed decision making and object interactions. State-of-the-art methods employ hand-crafted symbolic knowledge which is defined from a human perspective and grounded into sensory data afterwards. However, due to different sensing and acting capabilities of robots, t...