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Auflistung nach Schlagwort "AI literacy"

1 - 4 von 4
  • Konferenzbeitrag
    Assessment of AI literacy – Development and testing of a customizable set ofitems
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Faust, Anna; Dröge, Martin; Odebrecht, Carolin
    In this paper, we argue that there are two types of learners who seek to build AI literacy. However, recent studies that provide questionnaires to assess AI literacy seem suitable for one type of learners only. Based on previous literature, we generated items that also addresses the second type of learners. The items can be adapted to the needs of diverse fields. Further, in the following pages, we give insights in the preliminary result of evaluating AI literacy based on these items in the beginning of a course in summer term 2023. Results suggest, that students have very limited AI knowledge in the beginning of the course and lack a linkage of their knowledge.
  • Zeitschriftenartikel
    Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches
    (KI - Künstliche Intelligenz: Vol. 35, No. 2, 2021) Eguchi, Amy; Okada, Hiroyuki; Muto, Yumiko
    AI has become ubiquitous in our society, accelerated by the speed of the development of machine learning algorithms and voice and facial recognition technologies used in our everyday lives. Furthermore, AI-enhanced technologies and tools are no strangers in the field of education. It is more evident that it is important to prepare K-12 population of students for their future professions as well as citizens capable of understanding and utilizing AI-enhanced technologies in the future. In response to such needs, the authors started a collaborative project aiming to provide a K-12 AI curriculum for Japanese students. However, the authors soon realized that it is important to contextualize the learning experience for the targeted K-12 students. The paper aims at introducing the idea of contextualizing AI education and learning experience of K-12 students with examples and tips using the work-in-progress version of the contextualized curriculum using culturally responsive approaches to promote the awareness and understanding of AI ethics among middle school students.
  • Konferenzbeitrag
    An Immersive Learning Factory for AI & Data Literacy: An Exploratory Study in the Wild
    (Mensch und Computer 2023 - Tagungsband, 2023) Liu, Shi; Schulz, Thimo; Toreini, Peyman; Maedche, Alexander
    Artificial Intelligence (AI) has already made a strong impact on business and private life. Nonetheless, understanding how AI works and which role data plays in this context still remains unclear for many people. We argue that students with non-technical backgrounds should build up AI & data literacy to understand the key concepts of AI & data and leverage its potential in their field of study and research. For this purpose, we present the concept of an immersive learning factory, where students can explore AI & data concepts with interactive and immersive technologies. In this paper, we demonstrate our overarching idea, as well as the results of our exploratory evaluation with industrial engineering & management students from a data science lecture. Our main contribution includes the conceptual framework of the immersive learning factory, as well as design guidelines for creating immersive learning experiences concluded from the evaluation.
  • Konferenzbeitrag
    Understanding how Computers Learn: AI Literacy for Elementary School Learners
    (Proceedings of Mensch und Computer 2024, 2024) Simbeck, Katharina; Kalff, Yannick
    Elementary school learners regularly use artificial intelligence (AI) technologies like smart assistants. We discuss how young learners can acquire AI literacy skills related to the practical application, technical understanding, and critical appraisal of AI. We conceptualise a hands-on workshop on understanding how computers can be taught through programming and machine learning for learners without prior knowledge. We evaluate participants’ AI literacy quantitatively and qualitatively and find a large variance in interest, understanding, and knowledge in the relatively homogeneous groups. Our findings suggest that elementary school learners can understand basic machine learning concepts and gain ethical considerations, including data quality and bias. Given the importance of early AI education, the workshop concept can be implemented by teachers without formal computer science training, addressing the current limitation in AI education in elementary schools.