Artículo

Pedagogical incorporation of artificial intelligence in K-12 science education: A decadal bibliometric mapping and systematic literature review (2013-2023)

Resumen

Artificial intelligence (AI) technologies continue to revolutionize various sectors, including their incorporation into education, particularly in K-12 science education, which has become evidently significant. This paper presents a bibliometric analysis and systematic review that examines the incorporation of AI technologies in K-12 science education. A total of 20 studies, comprising journal articles and conference proceedings published between 2013 and 2023 and sourced from the Scopus database, were analyzed to identify leading journals, influential papers, and authors, and county-wise contributions. The study reveals that AI technologies, including robotics, chatbots, machine learning, automated scoring-feedback, and neural networks, have demonstrably enhanced learning outcomes, increased student engagement, and facilitated personalized education in science classrooms. Further, the review identifies diverse methodological approaches and pedagogical strategies, including hands-on learning, blended learning models, inquiry-based methods, and feedback-based learning, as practical means of incorporating AI within science classrooms. Moreover, the key findings emphasized the importance of professional development, infrastructure investment, and ethical guidelines to support equitable implementation of AI in science education. This study also advocates future research investigating long-term impacts, ethical considerations, and qualitative insights to fully understand AI’s potential in enhancing K-12 science education.
Lan, Xiaopeng (57223994524); Feng, Mei (59296864200); Chen, Lili (59296864300); Zhang, Luchen (59296987500); Han, Chao (59297228700); Wang, Yizhen (59297228800); Zheng, Jilu (59296737700); Wang, Xiaoyan (59297228900); Liu, Chunlei (57201500890); Liu, Ranlu (56571735100)
Trends in research on nanomedicine in urologic cancer: a bibliometric and visualized analysis
2024
10.1007/s12672-024-01249-w
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85201936958&doi=10.1007%2fs12672-024-01249-w&partnerID=40&md5=981ecdec040a9b699a6c8e111ac17d5e
Department of Urology, Tianjin Medical University General Hospital, Tianjin, China; Department of Urology, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, 266042, China
All Open Access; Gold Open Access
Scopus
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