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  9. »Learning About and Learning with Artificial Intelligence in School: From Understanding of Basic AI Concepts to Trustworthy and Human-centric AI Tools«
Ort: Paderborn
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»Learning About and Learning with Artificial Intelligence in School: From Understanding of Basic AI Concepts to Trustworthy and Human-centric AI Tools«

Prof. Dr. Ute Schmid at the »Paderborn Colloquium on Data Science and Artificial Intelligence in School«

Session No.08, Part 1:

Abstract
Artificial intelligence (AI) is currently a much discussed topic evoking high expectations as well as fears. For a realistic assessment of the opportunities and risks of AI, basic understanding of what makes AI applications different from other computer programs is necessary. How and what AI concepts can be introduced in primary and secondary education depends on the age and the computer science background of the students.
In the talk, a sample of topics and methods for introducing AI in school is presented – covering machine learning as well as automated reasoning, offering unplugged material for students without background in computer science as well as possibilities for more formal introduction of AI algorithms and AI programming. In the second part of the talk, learning analytics and intelligent tutor systems are introduced as applications of AI methods to support students and teachers. While learning analytics is mainly behavioristic with focus on applying machine learning to prediction of students’ performance, intelligent tutor systems are based on cognitive and constructivist principles with focus on AI methods for individualized diagnosis of misconceptions and feedback generation.

Bio Ute Schmid
Ute Schmid is a full professor of Cognitive Systems at University of Bamberg. She has master degrees both in computer science and in psychology.
For more than 20 years she has been teaching and researching artificial intelligence with special focus on machine learning and cognitive modeling. Ute Schmid dedicates a significant amount of her time to measures supporting women in computer science and to promote computer science as a topic in elementary, primary, and secondary education. She won the Minerva Informatics Equality Award 2018 of Informatics Europe for her university. Since many years, Ute Schmid is engaged in educating the public about artificial intelligence and she gives workshops for teachers as well as high-school students about AI and machine learning. Ute Schmid is speaker of the task force AI in Education of the Artificial Intelligence Section of the German Informatics Society (FBKI of GI). She is a member of the Bavarian AI council and a EurAI fellow.

Information on the colloquium (from the ProDaBi Website):
Data science, artificial intelligence, machine learning, data literacy, and statistical literacy concerning secondary education are currently discussed in the communities of scientists and educators in statistics, mathematics, computer science, social and natural sciences, and media education. Our colloquium intends to bring together these perspectives and communities to create an interdisciplinary community for scientific exchange.  

Since data science and artificial intelligence have become more and more relevant in industrial and economical automation processes, marketing processes, and monitoring in politics, both topics permeate nearly all areas of life. These influences raise questions about future possibilities for social participation, self-determination, and self-realization in the professional and private sector, resulting in the need for educational processes that address these issues in school. For the teaching of mathematics and computer science completely new challenges have emerged, as well as for the subjects of the socio-scientific field and cross-curricular media education. 

In our colloquium, we want to take up these issues and discuss state of the art and future trends of education in data science and artificial intelligence that can inspire ideas for teaching data science in secondary schools. We also want to discuss fundamental ideas of data science as they are conceptualized by experts in this field since a broad perspective of data science as a scientific discipline is needed to inform curriculum development. Contributions to the colloquium will also present practice-oriented research as well as research on teachers’ professional development.