Artificial Intelligence teaching and learning in K-12 from 2019 to 2022: A systematic literature review.

Autor/inn/en	Rizvi, Saman; Waite, Jane; Sentance, Sue
Titel	Artificial Intelligence teaching and learning in K-12 from 2019 to 2022: A systematic literature review.
Quelle	In: Computers and education: artificial intelligence, 2023 (2023) 4, 15 S. PDF als Volltext kostenfreie Datei (1); PDF als Volltext kostenfreie Datei (2) Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Zeitschriftenaufsatz
ISSN	2666-920X
DOI	10.1016/j.caeai.2023.100145
Schlagwörter	Evaluation; Systematic Review; Künstliche Intelligenz; Neue Technologien; Informatikunterricht; Kindertagesstätte; Künstliche Intelligenz; Lernen; Schule; Standardisierung; Evaluation; Lehren; Elementarbereich; Elementarbereich; Kindertagesstätte; Schule; Primarbereich; Sekundarbereich; Lernen; Lehren; Literaturanalyse; Informatikunterricht; Standardisierung
Abstract	"There is an emerging interest in Artificial Intelligence (AI) teaching and learning in the K-12 setting. While some work has explored the educational content and resources used for this purpose, there is limited empirical evidence on the effectiveness of such AI education interventions. The primary objective of the systematic literature review presented in this paper was to examine research with empirical evidence reporting learning outcomes for teaching and learning AI in K-12 between 2019 and 2022. (...) This paper outlines the focus on learners' context, the extent of empirical support for the pedagogical approaches, and the theoretical coverage of AI topics included in the studies. The majority of studies reported an improvement in both cognitive and affective learning outcomes. The paper concludes by highlighting key areas where additional research is needed in the future as well as the challenges associated with them. Although the findings are based on limited empirical studies, they suggest that a more learner-centred approach, context-aware pedagogical practices, and consistent constructs to measure AI learning outcomes could benefit teaching and learning AI in K-12 schools. " [Abstract: Authors' information].
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2024/1