ReviewHeliyon2024
Research perspectives and trends in Artificial Intelligence-enhanced language education: A review.
Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) has had a significant impact on language education, arousing the related studies from different fields and perspectives. However, the extant review articles only focused on a certain aspect in the field, thus neglecting the multi-disciplinary and multi-perspective features of AI-enhanced language education. The aim of the current study is to bridge this gap by reviewing the 812 articles selected from Web of Science via CiteSpace. The study found that the existing studies were mainly conducted from the perspectives of computer science, linguistics and psychology. Besides, the individualized development of language education supported by technology was not obvious, and the degree of human-computer interaction was weak. Moreover, previous studies focused more on the advantages of AI-enhanced language education than the disadvantages, and the empirical research to analyze specific problems was insufficient. In the future, the research tends to strengthen the cooperation among related disciplines and focus on the individualized development of language education. In addition, empirical research should be strengthened to explore the efficiency of AI-enhanced language education in order to promote the reform of language education.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.