@article {pub5791,
	title = {How to Design Interactive Physical Learning Robots That Are Fun to Teach: If You Are Curious, I Will Show You!},
	author = {Jan Leusmann AND Chao Wang AND Sven Mayer AND Michael Gienger AND Albrecht Schmidt},
	year = {2025},
	month = {July},
	abstract = {Recently, we have seen a rise in systems with various levels of autonomy, such as smart environments, robots, and cars. Teaching these systems effectively is crucial for making them useful, enforcing desired behavior, and correcting undesired actions. In-situ learning and adapting to specific contexts (e.g., culture, user type, preferences) are essential for effective real-world learning. Curiosity-driven behavior can lead to more natural interactions. However, motivating humans to teach machines is crucial.
Research Question: How can we make teaching technical systems easy, efficient, and enjoyable?
Central Challenge: How can we motivate people to teach their environment, smart objects, and robots? How can we design these systems to make teaching fun and engaging for long periods, encouraging users to show new things, correct actions, and explain their behavior to a system ? How can we make the learning process beneficial and enjoyable for humans? 
},
	publisher = {IEEE},
	journal = {IEEE Pervasive Computing}
}