Bibliometric Literature Review of Adaptive Learning Systems
Dionisios Koutsantonis; Konstantinos Koutsantonis; Nikolaos P. Bakas; Vagelis Plevris; Andreas Langousis; Savvas A. Chatzichristofis
In this review paper, we computationally analyze a vast volume of published articles in the field of Adaptive Learning, as obtained by the Scopus Database. Particularly, we use a query with search terms targeting the area of Adaptive Learning Systems by utilizing a combination of specific keywords. Accordingly, we apply a multidimensional scaling algorithm to construct bibliometric maps for keywords, authors, and references. Subsequently, we present the computational results for the studied dataset, reveal significant patterns appearing in the field of adaptive learning and the inter-item associations, and interpret the findings based on the current state-of-the-art literature in the area. Furthermore, we demonstrate the time-series of the evolution of the research terms, their trends over time, as well as their prevalent statistical associations.
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Эту запись предоставил Multidisciplinary Digital Publishing Institute
