Visualizing Artificial Intelligence Used in Education Over Two Decades

Visualizing Artificial Intelligence Used in Education Over Two Decades

Copyright: © 2020 |Pages: 15
DOI: 10.4018/JITR.2020100103
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Abstract

With the rapid development of computer science, use of artificial intelligence (AI) in education has caught much attention across the world although it is still a young field with many under-explored research elements. Through visualizing study with bibliometric evaluation and taxonomy of the literature using both VOSviewer and CiteSpace, this study provided references for readers in terms of cluster mapping on the basis of keywords, bibliographic coupling of countries, cluster mapping on the basis of co-citations, citation counts, bursts, betweenness centrality, and sigma. Researchers could also take the findings of this study into serious consideration when they set about researching effectiveness, efficiency, or usefulness of AI in education. Future research into use of AI in education will most likely need interdisciplinary cooperation between computer science, statistics, education, cognition, and robotics.
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Literature Review

Use of AI in General Education

Based on the previous publications with high citations, it is undoubted that major AI-based devices have been widely used in educational field. A Bayesian network model was proposed to detect students’ specific learning styles in an Artificial Intelligence Online Course. The model was demonstrated effective in determining students’ different learning styles (Garcia, Amandi, & Schiaffino, 2007). AI has also been introduced into the field of higher education, despite that numerous teaching staff are unfamiliar with its scope and contents. For example, an intelligent robot “Sage” was designed and stationed at the Carnegie Museum of Natural History to offer educational information to visitors (Nourbakhsh, Bobenage, Grange, Lutz, Meyer, & Soto, 1999). There is a world-wide intense interest in AI use in higher education, although AI related products especially used in higher education have not yet been immensely developed (Hinojo-Lucena, Aznar-Diaz, Caceres-Reche, & Romero-Rodriguez, 2019).

Many scientists have been committed to development of an intelligent tutoring system, after which an advanced learning companion system was developed. Different from the intelligent tutoring system, where a computer plays the role as an intelligent instructor, the learning companion system acts as both an intelligent instructor and as a learning companion, e.g. Virtual Companion System (VCS) (Hsieh, & Wu, 2013), and Confucius (Hsieh, 2011). This new learning companion learning system, applied to education in various fields, has attracted much attention in the academia due to its effectiveness and high efficiency.

Use of AI in Physical Education

Teaching Result Evaluation was designed to evaluate teaching quality in physics based on specific principles, data, mathematical model and human-computer interaction model under the framework of AI expert decision system. It is reported that Teaching Result Evaluation can successfully provide theoretical foundation for decision making, positively influence the reform and improve teaching quality of physical education (Wen, 2018).

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