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What Students Can Learn About Artificial Intelligence -- Recommendations for K-12 Computing Education

2023/05/10 by Tilman Michaeli, Michaeli, Tilman, Stefan Seegerer +3
Computer Science · #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #Education and Learning Interventions #Educational Research and Pedagogy #FOS: Computer and information sciences #I.2.0 #K.3.2 #Teaching and Learning Programming

paper · pdf · doi:10.48550/arxiv.2305.06450

openalex publication_date 2023/05/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Technological advances in the context of digital transformation are the basis for rapid developments in the field of artificial intelligence (AI). Although AI is not a new topic in computer science (CS), recent developments are having an immense impact on everyday life and society. In consequence, everyone needs competencies to be able to adequately and competently analyze, discuss and help shape the impact, opportunities, and limits of artificial intelligence on their personal lives and our society. As a result, an increasing number of CS curricula are being extended to include the topic of AI. However, in order to integrate AI into existing CS curricula, what students can and should learn in the context of AI needs to be clarified. This has proven to be particularly difficult, considering that so far CS education research on central concepts and principles of AI lacks sufficient elaboration. Therefore, in this paper, we present a curriculum of learning objectives that addresses digital literacy and the societal perspective in particular. The learning objectives can be used to comprehensively design curricula, but also allow for analyzing current curricula and teaching materials and provide insights into the central concepts and corresponding competencies of AI.

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