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Significant Changes to Course Grading:

This course will no longer be (partially) evaluated through an exam. We will keep the partial grading by a team-based capstone project and substitute the exam part through other individual outputs, such as presentations in a Flipped-Classroom format. This also means that all relevant aspects for grading can be completed during the lecture period. Specifics on the formats used for grading, timeline, mandatory sessions to participate, and evaluation criteria will be shared in the first lecture and are partially available already in the ILIAS course beforehand. 

Further, you will need to register for one of the 35 limited participant spots for this course after the first lecture. Please make sure you can attend the first lecture to obtain information on how to sign up/apply for this course.

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The field of computing has transitioned from traditional batch processing toward the development of highly sophisticated interactive and intelligent systems. As artificial intelligence (AI) continues to advance, these systems have gained the capacity to learn, adapt to environmental stimuli, and simulate human cognitive processes. While the capacity of AI-based information technology to augment and automate human tasks has expanded, it simultaneously creates complex new demands for the design of interactive systems and necessitates a sophisticated understanding of the nuances within human-AI interaction.

This Master’s course explores the state-of-the-art scientific knowledge and practical applications required to navigate these complexities, specifically focusing on the design of AI-based interactive systems for personal productivity on the individual level and virtual collaboration on the team level within professional environments.The course is divided into two phases: The first phase establishes a scientific foundation through a flipped classroom model. Students engage with conceptual foundations and theoretical frameworks independently, allowing in-person sessions to be dedicated to analysis and critical discussion of existing knowledge for designing interactive systems enabling effective human-AI interaction. The second phase transitions into the practical application of these concepts through a collaborative capstone project conducted in partnership with an industry partner. In this phase, students work in teams to apply knowledge acquired in the first phase culminating in the creation of a prototype of an interactive system. The project emphasizes the intricacies of human-AI interaction, requiring students to synthesize their theoretical knowledge into a functional and sophisticated design solution.

Learning objectives:

• Evaluate existing theories and conceptual frameworks of interactive systems to assess their role in modern computing environments.
• Analyze the unique characteristics of human-AI interaction and determine their impact on future interactive systems design.
• Create a functional interactive prototype by following the human-centered design process and applying state-of-the-art knowledge within a collaborative capstone project to solve real-world problems.
• Get hands-on experience by applying lecture content in a design capstone project

Prerequisites: No specific prerequisites are required for the lecture

Literature: Further literature will be made available in the lecture.  

Die Erfolgskontrolle erfolgt in Form einer Prüfungsleistung anderer Art (Form) nach § 4 Abs. 2 Nr. 3 SPO. Details zur Ausgestaltung der Erfolgskontrolle werden im Rahmen der Vorlesung bekannt gegeben.

Language of instruction: English

Contact: Adrian Wegener (adrian.wegener@kit.edu)