Mapping the Literature on Intelligent Systems and Decision Support in Higher Education: A Bibliometric Analysis

Abstract

Despite the growth of literature on intelligent systems and decision support in higher education, a gap remains regarding the mapping of this scientific field. This paper thereby aims to map the literature pertaining to this domain through a comprehensive bibliometric analysis which we conducted in three steps: data collection, data processing and extraction of results. A total of 99 articles were analyzed, consisting of 51 from Scopus and 48 from WoS. The selection criteria included works published between the years 2018 to 2022 which focused on specific keywords: "Intelligent Systems," "Decision Support," and "Higher Education". Our analysis encompassed conference papers, conference reviews, and reviews. The findings revealed a significant growth trend in the field over the five-year period with research being concentrated in five key areas: data mining techniques for decision support, integration of artificial intelligence and intelligent tutoring systems, exploration of information systems and neural networks, application of artificial intelligence in Industry 4.0, and analysis of learning and e-learning. The study identified both the sources of publications and the contributing authors, considering not only the quantity of documents but also their relevance based on citation indexes. Although China and the USA emerged as the leading countries in publishing research in this field. these findings provide valuable insight for researchers worldwide since bibliometric mapping offers a comprehensive overview of a scientific field and may guide future research directions.