scholarly journals A Bibliometric Analysis of the Papers Published in the Journal of Artificial Intelligence in Education from 2015-2019

2020 ◽  
Vol 2 (1) ◽  
pp. 67
Author(s):  
Clare Baek ◽  
Tenzin Doleck
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
International Collaboration ◽  
Web Of Science ◽  
Collaboration Network ◽  
Collaboration Networks ◽  
International Partnership ◽  
Artificial Intelligence In Education ◽  
Prolific Authors ◽  
Institutional Network

To analyze the current research status and trends of the artificial intelligence in education field, we applied bibliometric methods to examine the articles published in one of the representative journals of the field, <em>International Journal of Artificial Intelligence in Education, </em>from 2015 to 2019. We analyzed 135 articles retrieved from the Web of Science database and examined prolific countries, collaboration networks, prolific authors, keywords, and the citations the articles received. Through examining keywords, we found that the authors largely focused on students and learning. Through examining prolific authors and countries, we found active publication of corresponding authors from United States, United Kingdom, Canada, and Germany. We found international collaboration among some researchers and institutions, such as strong collaboration network between United States and Canada. We suggest reinforcement in building more widespread international partnership and expanding collaboration network by including diverse institutions. International collaboration and expanded institutional network can improve research by incorporating various perspectives and expertise.

scholarly journals A Strategic View for Rare Earths Production, in a Competitive and Sustainable form

2016 ◽  
Vol 6 (4) ◽  
pp. 140
Author(s):  
Tereza Raquel Taulois Campos ◽  
Marcus Vinicius de Araujo Fonseca ◽  
Bruna de Paula Fonseca e Fonseca ◽  
Edison de Oliveira Martins F
Keyword(s):  
Rare Earths ◽  
Scientific Collaboration ◽  
Web Of Science ◽  
Electronic Equipment ◽  
Collaboration Network ◽  
Scientific Publications ◽  
Industrial Solid Waste ◽  
Alternative Sources ◽  
Institutional Network ◽  
Network Collaboration

The demand for rare earths (RE) has been intensified by their large use, especially in high technology sectors. Supply difficulties have forced RE users to seek alternative sources and invest in the development of recycling technologies and options of reuse for these elements. This article seeks to reveal the trends and ongoing changes in national and global prospects of RE. Additionally, it aims to analyze scientific collaboration networks in the area of industrial solid waste (ISW) and waste electrical and electronic equipment (WEEE) exploitation in Brazil, examining both researchers and institutions with greater representation in the field. For this purpose, social network analysis methods were used to build and analyze co-authorship networks based on scientific publications retrieved from the Web of Science (WoS) database. The results showed that the Brazilian collaboration network of ISW research was extremely fragmented and contained 105 different groups, which were not connected to each other. The institutional network of ISW research was composed of 125 institutions, 75.2% of them from Brazil. The Brazilian collaboration network of research in WEEE was small (37 researchers), but fragmented: researchers were divided into eight different groups that do not connect to each other. The institutional network of research in WEEE was composed by 12 institutions, nine of them from Brazil. Therefore, this article presents a network collaboration model to bring together actors involved in the management of waste electrical and electronic equipment (WEEE), emphasizing the potential for recovery of RE from these wastes, with the purpose of developing products and services. 

scholarly journals A Look at the Past, Present and Future Research Trends of Artificial Intelligence in Agriculture

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1839
Author(s):  
José Luis Ruiz-Real ◽  
Juan Uribe-Toril ◽  
José Antonio Torres Arriaza ◽  
Jaime de Pablo Valenciano
Keyword(s):  
Artificial Intelligence ◽  
Web Of Science ◽  
Scientific Literature ◽  
Green Economy ◽  
Future Research ◽  
Agriculture Sector ◽  
The Past ◽  
Use Of Resources ◽  
Research Organizations ◽  
Prolific Authors

Technification in agriculture has resulted in the inclusion of more efficient companies that have evolved into a more complex sector focused on production and quality. Artificial intelligence, one of the relevant areas of technology, is transforming the agriculture sector by reducing the consumption and use of resources. This research uses a bibliometric methodology and a fractional counting method of clustering to analyze the scientific literature on the topic, reviewing 2629 related documents recorded on the Web of Science and Scopus databases. The study found significant results regarding the most relevant and prolific authors (Hoogenboom), supporting research organizations (National Natural Science Foundation of China) and countries (U.S., China, India, or Iran). The identification of leaders in this field gives researchers new possibilities for new lines of research based on previous studies. An in-depth examination of authors’ keywords identified different clusters and trends linking Artificial Intelligence and green economy, sustainable development, climate change, and the environment.

Scientometrics Analysis of Contributions to Journal of Artificial Intelligence Research During 2010-2016

2018 ◽  
Vol 8 (1) ◽  
pp. 58-63
Author(s):  
Vimlesh Patel
Keyword(s):  
Artificial Intelligence ◽  
Geographical Distribution ◽  
Growth And Development ◽  
Web Of Science ◽  
Scientometric Analysis ◽  
Authorship Pattern ◽  
Artificial Intelligence Research ◽  
University Of Oxford ◽  
Prolific Authors

The paper presents a Scientometric analysis of papers published in Journal of Artificial Intelligence Research, during 2010 to 2016 as reflected in Web of Science database. It attempts to analyze the growth and development of publications output of Journal of Artificial Intelligence Research as reflected. Data for a total of 402 have been downloaded and analyzed according to objectives. The study reveals that the year wise growth of literature in terms of total papers, most preferred authorship pattern was two authors, highly prolific authors and their publications revel that Jennings NR, published highest numbers of papers, the geographical distribution contributions (International) is revel that USA is in the top with no. of publications is 138 (34.33%), followed by England 56 (13.93%) as a second position and Germany with no. of publication is 42 (10.45%) in third position and institution-wise distribution of papers shows that highest contributed institutions was University of Oxford with 17 Publications (04.23%) is placed at 1st rank.

scholarly journals Artificial Intelligence in Education: A Bibliometric Study

2021 ◽  
pp. 822-837
Author(s):  
Tarik Talan
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Web Of Science ◽  
State University ◽  
Arizona State University ◽  
Tutoring Systems ◽  
University Of Memphis ◽  
Artificial Intelligence In Education ◽  
The Usa ◽  
The Subject

The aim of this study is to examine the studies in the literature on the use of artificial intelligence in education in terms of its bibliometric properties. The Web of Science (WoS) database was used to collect the data. Various keywords were used to search the literature, and a total of 2,686 publications on the subject published between 2001-2021 were found. The inquiry revealed that most of the studies were carried out in the USA. According to the results, it was seen that the most frequently published journals were Computers Education and International Journal of Emerging Technologies in Learning. The study showed that the institutions of the authors were in the first place as Carnegie Mellon University, University of Memphis and Arizona State University as the most productive organizations due to the number of their publications, while Vanlehn, K. and Chen, C. –M. were the most effective and productive researchers. As a result of the analysis, it was determined that the co-authorship network structure was predominantly USA, Taiwan and United Kingdom. In addition, when the keywords mentioned together were mapped, it was seen that the words artificial intelligence, intelligent tutoring systems, machine learning, deep learning and higher education were used more frequently.

scholarly journals Artificial Intelligence in education: Using heart rate variability (HRV) as a biomarker to assess emotions objectively

2021 ◽  
Vol 2 ◽  
pp. 100011
Author(s):  
Joanne Wai Yee Chung ◽  
Henry Chi Fuk So ◽  
Marcy Ming Tak Choi ◽  
Vincent Chun Man Yan ◽  
Thomas Kwok Shing Wong
Keyword(s):  
Artificial Intelligence ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Artificial Intelligence In Education

scholarly journals Is academia becoming more localised? The growth of regional knowledge networks within international research collaboration

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
John Fitzgerald ◽  
Sanna Ojanperä ◽  
Neave O’Clery
Keyword(s):  
Economic Development ◽  
International Collaboration ◽  
International Research ◽  
Research Collaboration ◽  
Learning By Doing ◽  
Knowledge Networks ◽  
Collaboration Network ◽  
International Research Collaboration ◽  
The Past ◽  
Capability Building

AbstractIt is well-established that the process of learning and capability building is core to economic development and structural transformation. Since knowledge is ‘sticky’, a key component of this process is learning-by-doing, which can be achieved via a variety of mechanisms including international research collaboration. Uncovering significant inter-country research ties using Scopus co-authorship data, we show that within-region collaboration has increased over the past five decades relative to international collaboration. Further supporting this insight, we find that while communities present in the global collaboration network before 2000 were often based on historical geopolitical or colonial lines, in more recent years they increasingly align with a simple partition of countries by regions. These findings are unexpected in light of a presumed continual increase in globalisation, and have significant implications for the design of programmes aimed at promoting international research collaboration and knowledge diffusion.

scholarly journals Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021

AI and Ethics ◽  
2021 ◽  
Author(s):  
Muhammad Ali Chaudhry ◽  
Emre Kazim
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Policy Makers ◽  
Tutoring Systems ◽  
Research And Practice ◽  
The Past ◽  
Artificial Intelligence In Education ◽  
Potential Impact ◽  
High Level ◽  
Contextualized Learning

AbstractIn the past few decades, technology has completely transformed the world around us. Indeed, experts believe that the next big digital transformation in how we live, communicate, work, trade and learn will be driven by Artificial Intelligence (AI) [83]. This paper presents a high-level industrial and academic overview of AI in Education (AIEd). It presents the focus of latest research in AIEd on reducing teachers’ workload, contextualized learning for students, revolutionizing assessments and developments in intelligent tutoring systems. It also discusses the ethical dimension of AIEd and the potential impact of the Covid-19 pandemic on the future of AIEd’s research and practice. The intended readership of this article is policy makers and institutional leaders who are looking for an introductory state of play in AIEd.

The ideological divide in public perceptions of self-driving cars

2020 ◽  
Vol 29 (4) ◽  
pp. 436-451
Author(s):  
Yilang Peng
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Scientific Literacy ◽  
Autonomous Vehicles ◽  
The United States ◽  
Public Perceptions ◽  
New Information ◽  
Nationally Representative ◽  
Self Driving Cars ◽  
Social Conservatism

Applications in artificial intelligence such as self-driving cars may profoundly transform our society, yet emerging technologies are frequently faced with suspicion or even hostility. Meanwhile, public opinions about scientific issues are increasingly polarized along the ideological line. By analyzing a nationally representative panel in the United States, we reveal an emerging ideological divide in public reactions to self-driving cars. Compared with liberals and Democrats, conservatives and Republicans express more concern about autonomous vehicles and more support for restrictively regulating autonomous vehicles. This ideological gap is largely driven by social conservatism. Moreover, both familiarity with driverless vehicles and scientific literacy reduce respondents’ concerns over driverless vehicles and support for regulation policies. Still, the effects of familiarity and scientific literacy are weaker among social conservatives, indicating that people may assimilate new information in a biased manner that promotes their worldviews.

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