Teaching Machine Learning in School: A Systematic Mapping of the State of the Art

• Published in: Informatics in education Vol. 19; no. 2; pp. 283 - 321
• Main Authors: Marques, Lívia S, Gresse von Wangenheim, Christiane, Hauck, Jean Carlo Rossa
• Format: Journal Article
• Language: English
• Published: Vilnius Vilniaus Universiteto Leidykla 2020; Vilnius University Press; Institute of Mathematics and Informatics; Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences; Vilnius University
• Subjects: Algorithms; Artificial Intelligence; Computer science; Computers; Curricula; Education; Educational Technology; Elementary Secondary Education; Extracurricular Activities; Faculty Development; Guidelines; High School Students; Higher education; ICT Information and Communications Technologies; Imagery; Informatics; Information Science; Initiatives; Instructional Materials; k-12; Literacy; Machine learning; Man Machine Systems; Mapping; Mathematical Models; Neural networks; Oral Language; Secondary schools; Skill Development; Society; Software; State-of-the-art reviews; Statistical Inference; Students; Teaching; Teaching machines; Teaching Methods; Technology Uses in Education; Units of Study; Machine Learning; K12; teaching
• ISSN: 1648-5831; 2335-8971
• DOI: 10.15388/infedu.2020.14

Although Machine Learning (ML) is integrated today into various aspects of our lives, few understand the technology behind it. This presents new challenges to extend computing education early to ML concepts helping students to understand its potential and limits. Thus, in order to obtain an overview...