A Review of AI Teaching and Learning from 2000 to 2020

Autor/inn/en	Ng, Davy Tsz Kit; Lee, Min; Tan, Roy Jun Yi; Hu, Xiao; Downie, J. Stephen; Chu, Samuel Kai Wah
Titel	A Review of AI Teaching and Learning from 2000 to 2020
Quelle	In: Education and Information Technologies, 28 (2023) 7, S.8445-8501 (57 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-022-11491-w
Schlagwörter	Artificial Intelligence; Technology Uses in Education; Technological Literacy; Literacy Education; Computer Science Education; Higher Education; Elementary Secondary Education; Cooperative Learning; Student Projects; Active Learning; Computer Software; Problem Solving; Robotics; Game Based Learning; Programming; Teaching Methods; Interdisciplinary Approach; Curriculum Design + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Technisches Wissen; Computer science lessons; Informatikunterricht; Hochschulbildung; Hochschulsystem; Hochschulwesen; Kooperatives Lernen; Schulprojekt; Aktives Lernen; Problemlösen; Robotertechnik; Programmierung; Teaching method; Lehrmethode; Unterrichtsmethode; Fächerübergreifender Unterricht; Fächerverbindender Unterricht; Interdisziplinarität; Lehrplangestaltung
Abstract	In recent years, with the popularity of AI technologies in our everyday life, researchers have begun to discuss an emerging term "AI literacy". However, there is a lack of review to understand how AI teaching and learning (AITL) research looks like over the past two decades to provide the research basis for AI literacy education. To summarize the empirical findings from the literature, this systematic literature review conducts a thematic and content analysis of 49 publications from 2000 to 2020 to pave the way for recent AI literacy education. The related pedagogical models, teaching tools and challenges identified help set the stage for today's AI literacy. The results show that AITL focused more on computer science education at the university level before 2021. Teaching AI had not become popular in K-12 classrooms at that time due to a lack of age-appropriate teaching tools for scaffolding support. However, the pedagogies learnt from the review are valuable for educators to reflect how they should develop students' AI literacy today. Educators have adopted collaborative project-based learning approaches, featuring activities like software development, problem-solving, tinkering with robots, and using game elements. However, most of the activities require programming prerequisites and are not ready to scaffold students' AI understandings. With suitable teaching tools and pedagogical support in recent years, teaching AI shifts from technology-oriented to interdisciplinary design. Moreover, global initiatives have started to include AI literacy in the latest educational standards and strategic initiatives. These findings provide a research foundation to inform educators and researchers the growth of AI literacy education that can help them to design pedagogical strategies and curricula that use suitable technologies to better prepare students to become responsible educated citizens for today's growing AI economy. (As Provided).
Anmerkungen	Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01