A systematic review of teaching and learning machine learning in K-12 education

• Published in: Education and information technologies Vol. 28; no. 5; pp. 5967 - 5997
• Main Authors: Sanusi, Ismaila Temitayo, Oyelere, Solomon Sunday, Vartiainen, Henriikka, Suhonen, Jarkko, Tukiainen, Markku
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.05.2023; Springer; Springer Nature B.V
• Subjects: Artificial Intelligence; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computers and Education; Curriculum Development; Distribuerade datorsystem; Education; Educational Practices; Educational Research; Educational Resources; Educational Technology; Educational Trends; Elementary Secondary Education; Ethics; Faculty Development; Informal Education; Information Systems Applications (incl.Internet); Instructional Development; K-12; Kindergarten; Learning; Machine learning; Middle Schools; Pedagogy; Pervasive Mobile Computing; Professional development; Research Needs; Social Change; Systematic review; Teacher Improvement; Teacher Qualifications; Teachers; Teaching; User Interfaces and Human Computer Interaction; Finland; K-12; Systematic review; Artificial intelligence; Machine learning
• ISSN: 1360-2357; 1573-7608; 1573-7608
• DOI: 10.1007/s10639-022-11416-7

The increasing attention to Machine Learning (ML) in K-12 levels and studies exploring a different aspect of research on K-12 ML has necessitated the need to synthesize this existing research. This study systematically reviewed how research on ML teaching and learning in K-12 has fared, including the current area of focus, and the gaps that need to be addressed in the literature in future studies. We reviewed 43 conference and journal articles to analyze specific focus areas of ML learning and teaching in K-12 from four perspectives as derived from the data: curriculum development, technology development, pedagogical development, and teacher training/professional development. The findings of our study reveal that (a) additional ML resources are needed for kindergarten to middle school and informal settings, (b) further studies need to be conducted on how ML can be integrated into subject domains other than computing, (c) most of the studies focus on pedagogical development with a dearth of teacher professional development programs, and (d) more evidence of societal and ethical implications of ML should be considered in future research. While this study recognizes the present gaps and direction for future research, these findings provide insight for educators, practitioners, instructional designers, and researchers into K-12 ML research trends to advance the quality of the emerging field.