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Bibliometric Literature Review of Adaptive Learning Systems

Dionisios Koutsantonis, Konstantinos Koutsantonis, Nikolaos P. Bakas (), Vagelis Plevris, Andreas Langousis and Savvas A. Chatzichristofis ()
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Dionisios Koutsantonis: Research and Development Department, RDC Informatics, 10442 Athens, Greece
Konstantinos Koutsantonis: Research and Development Department, RDC Informatics, 10442 Athens, Greece
Nikolaos P. Bakas: Research and Development Department, RDC Informatics, 10442 Athens, Greece
Vagelis Plevris: Department of Civil and Architectural Engineering, Qatar University, Doha P.O. Box 2713, Qatar
Andreas Langousis: Department of Civil Engineering, University of Patras, 26504 Patras, Greece
Savvas A. Chatzichristofis: Intelligent Systems Laboratory, Department of Computer Science, Neapolis University Pafos, Pafos 8042, Cyprus

Sustainability, 2022, vol. 14, issue 19, 1-18

Abstract: 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.

Keywords: adaptive learning; intelligent tutoring systems; personalized learning; machine learning; bibliometrics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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