Mapping the landscape: A bibliometric analysis of AI and teacher collaboration in educational research.

Q2 Pharmacology, Toxicology and Pharmaceutics
F1000Research Pub Date : 2025-05-01 eCollection Date: 2025-01-01 DOI:10.12688/f1000research.160297.2
Arvind Nain, N S Bohra, Archana Singh, Rekha Verma, Rakesh Kumar, Rajesh Kumar
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引用次数: 0

Abstract

Background: This study intends to investigate the relationship between artificial intelligence and teachers' collaboration in educational research in response to the growing use of technologies and the current status of the field.

Methods: A total of 62 publications were looked at through a systematic review that included data mining, analytics, and bibliometric methods.

Result: The study shows a steady increase in the field of artificial intelligence and teacher collaboration in educational research, especially in the last few years with the involvement of the USA, China, and India. Education and information technology are the main contributors to this field of study, followed by an international review of open and distance learning research. The Scopus database was chosen for this study because of its extensive coverage of high-quality, peer-reviewed literature and robust indexing system, making it a dependable source for conducting bibliometric analyses. Scopus offers substantial information, citations tracking, and multidisciplinary coverage, which are critical for spotting publication trends, significant articles, major themes, and keywords in the area. The findings show that education and information technology make the most significant contributions to this sector, followed by international studies on open and distance learning.

Conclusions: Over a three-year period, the average citation value is 12.44%. The education system, learning, e-learning, sustainability, COVID-19 issues, team challenges, organizational conflicts, and digital transformation are just a few of the topics it significantly contributes to. The study acknowledges its limitations and considers potential avenues for additional research. The results also emphasize important gaps in the literature, highlighting the necessity for more research. This information can help develop strategic approaches to address issues and take advantage of opportunities relating to artificial intelligence and teacher collaboration in higher education and research. The study's ultimate goal is to offer guidance for tactics that promote teachers' cooperation in educational research and the development of artificial intelligence.

绘制景观:人工智能与教育研究中教师合作的文献计量分析。
背景:本研究旨在探讨人工智能与教师在教育研究中的合作关系,以应对日益增长的技术使用和该领域的现状。方法:通过包括数据挖掘、分析和文献计量学方法在内的系统综述,共观察了62份出版物。结果:该研究表明,人工智能领域和教师在教育研究中的合作稳步增长,特别是在过去几年中,美国、中国和印度的参与。教育和信息技术是这一研究领域的主要贡献者,其次是对开放和远程学习研究的国际审查。之所以选择Scopus数据库进行这项研究,是因为它广泛覆盖了高质量的同行评议文献和强大的索引系统,使其成为进行文献计量分析的可靠来源。Scopus提供了大量的信息、引用跟踪和多学科覆盖,这对于发现该领域的出版趋势、重要文章、主要主题和关键字至关重要。调查结果显示,教育和信息技术对这一领域的贡献最大,其次是关于开放和远程学习的国际研究。结论:3年平均被引值为12.44%。教育系统、学习、电子学习、可持续性、COVID-19问题、团队挑战、组织冲突和数字化转型只是它重要贡献的几个主题。该研究承认其局限性,并考虑了进一步研究的潜在途径。研究结果还强调了文献中的重要空白,强调了进行更多研究的必要性。这些信息可以帮助制定解决问题的战略方法,并利用与高等教育和研究中的人工智能和教师合作有关的机会。本研究的最终目的是为促进教师在教育研究和人工智能发展中的合作提供策略指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
F1000Research
F1000Research Pharmacology, Toxicology and Pharmaceutics-Pharmacology, Toxicology and Pharmaceutics (all)
CiteScore
5.00
自引率
0.00%
发文量
1646
审稿时长
1 weeks
期刊介绍: F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities. F1000Research is a scholarly publication platform set up for the scientific, scholarly and medical research community; each article has at least one author who is a qualified researcher, scholar or clinician actively working in their speciality and who has made a key contribution to the article. Articles must be original (not duplications). All research is suitable irrespective of the perceived level of interest or novelty; we welcome confirmatory and negative results, as well as null studies. F1000Research publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others. Reviews and Opinion articles providing a balanced and comprehensive overview of the latest discoveries in a particular field, or presenting a personal perspective on recent developments, are also welcome. See the full list of article types we accept for more information.
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