首页|Data on Machine Learning Described by Researchers at University of Johannesburg (Analyzing the evolution of machine learning integration in educational research : a bibliometric perspective)
Data on Machine Learning Described by Researchers at University of Johannesburg (Analyzing the evolution of machine learning integration in educational research : a bibliometric perspective)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intell igence are discussed in a new report. According to news reporting out of the Uni versity of Johannesburg by NewsRx editors, research stated, "Machine learning, a subset of artificial intelligence, has experienced rapid advancements and appli cations across various domains. In education, its integration holds great potent ial to revolutionize teaching, learning, and educational outcomes." The news reporters obtained a quote from the research from University of Johanne sburg: "Despite the growing interest, there needs to be more comprehensive bibli ometric analyses that track the trajectory of machine learning's integration int o educational research. This study addresses this gap by providing a nuanced per spective derived from bibliometric insights. Using a dataset from 1986 to 2022, consisting of 449 documents from 145 sources retrieved from the Web of Science ( WoS), the research employs network analysis to unveil collaborative clusters and identify influential authors. A temporal analysis of annual research output she ds light on evolving trends, while a thematic content analysis explores prevalen t research themes through keyword frequency. The findings reveal that co-authors hip network analysis exposes distinct clusters and influential figures shaping t he landscape of machine learning in educational research. Scientific production over time reveals a significant surge in research output, indicating the field's maturation. The co-occurrence analysis emphasizes a collective focus on student -centric outcomes and technology integration, with terms like ‘online' and ‘anal ytics' prevailing. This study provides a nuanced understanding of the collaborat ive and thematic fabric characterizing machine learning in educational research. The implications derived from the findings guide strategic collaborations, emph asizing the importance of cross-disciplinary engagement."
University of JohannesburgCyborgsEme rging TechnologiesMachine Learning
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