An Intelligent Multi-Criteria Decision Approach for Selecting the Optimal Operating System for Educational Environments

The selection of an appropriate operating system (OS) in educational environments is a critical decision that impacts the functionality, user experience, and overall efficiency. Financial factors, along with the availability and functionality of tools used on these systems, play a crucial role in this selection. Furthermore, the OS affects the user experience, security, and adaptability to learning. Previous research in this area is scarce, and this paper contributes to a better understanding of the OS selection process in education. This paper proposes a novel multi-criteria decision-making approach to evaluate and select the most suitable OS for educational institutions. The methodology integrates the PIPRECIA method for assessing weighted criteria, alongside utility analysis (NWA), enabling a balanced decision-making process between institutional management and IT experts. The evaluation considered the following criteria: performance, cost, security, usability, implementation, support, and documentation. The study compared three popular operating systems: Microsoft Windows 11, GNU Linux Ubuntu 22.04 LTS, and Apple macOS 12 using the proposed approach. The results, based on the integrated evaluation of all criteria, indicate that GNU Linux Ubuntu 22.04 LTS (0.562) ranked highest, followed by Microsoft Windows 11 (0.553) and Apple macOS 12 (0.543). This paper emphasizes the importance of objective, group-based decision-making in selecting an OS for education, providing practical insights and guidelines for effective technology integration in academic settings.

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Publication Details

Journal
Electronics
Published
2025-01-27
DOI
https://doi.org/10.3390/electronics14030514
Citations
4
Primary Topic
Advanced Data Processing Techniques
Type
article
Field-Weighted Citation Impact
4.86
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article

An Intelligent Multi-Criteria Decision Approach for Selecting the Optimal Operating System for Educational Environments

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4 citations
Electronics
Advanced Data Processing Techniques
4.86
article

An Intelligent Multi-Criteria Decision Approach for Selecting the Optimal Operating System for Educational Environments

Ana Bašić, Dragan Rastovac, Dejan Viduka, Igor Lavrnić, Petra Balaban, Aleksandar Skulić, Bojan Stojčetović, Minja Marinović
article en
4 citations

Abstract

The selection of an appropriate operating system (OS) in educational environments is a critical decision that impacts the functionality, user experience, and overall efficiency. Financial factors, along with the availability and functionality of tools used on these systems, play a crucial role in this selection. Furthermore, the OS affects the user experience, security, and adaptability to learning. Previous research in this area is scarce, and this paper contributes to a better understanding of the OS selection process in education. This paper proposes a novel multi-criteria decision-making approach to evaluate and select the most suitable OS for educational institutions. The methodology integrates the PIPRECIA method for assessing weighted criteria, alongside utility analysis (NWA), enabling a balanced decision-making process between institutional management and IT experts. The evaluation considered the following criteria: performance, cost, security, usability, implementation, support, and documentation. The study compared three popular operating systems: Microsoft Windows 11, GNU Linux Ubuntu 22.04 LTS, and Apple macOS 12 using the proposed approach. The results, based on the integrated evaluation of all criteria, indicate that GNU Linux Ubuntu 22.04 LTS (0.562) ranked highest, followed by Microsoft Windows 11 (0.553) and Apple macOS 12 (0.543). This paper emphasizes the importance of objective, group-based decision-making in selecting an OS for education, providing practical insights and guidelines for effective technology integration in academic settings.

ElectronicsVol. 14(3)
University of Novi Sad (RS), University of Belgrade (RS), Belgrade Open School (RS), Univerzitet Privredna akademija u Novom Sadu
Openalex Percentile: Top 6%
Advanced Data Processing Techniques
4.86
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