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An Intuitionistic Fuzzy Consensus WASPAS Method for Assessment of Open-Source Software Learning Management Systems
Volume 34, Issue 3 (2023), pp. 529–556
Pub. online: 28 August 2023      Type: Research Article      Open accessOpen Access
Received
1 May 2023
Accepted
1 August 2023
Published
28 August 2023

Abstract

Ineffective evaluation of open-source software learning management system (OSS-LMS) packages can negatively impact organizational effectiveness. Clients may struggle to select the best OSS-LMS package from a wide range of options, leading to a complex multi-criteria group decision-making (MCGDM) problem. This evaluates OSS-LMS packages based on several criteria like usability, functionality, e-learning standards, reliability, activity tracking, course development, assessment, backup and recovery, error reporting, efficiency, operating system compatibility, computer-managed instruction, authentication, authorization, troubleshooting, maintenance, upgrading, and scalability. Handling uncertain data is a vital aspect of OSS-LMS package evaluation. To tackle MCGDM issues, this study presents a consensus weighted sum product (c-WASPAS) method which is applied to an educational OSS-LMS package selection problem to evaluate four OSS-LMS packages, namely ATutor, eFront, Moodle, and Sakai. The findings indicate that the priority order of alternatives is Moodle > Sakai > eFront > ATutor and, therefore, MOODLE is the best OSS-LMS package for the case study. A sensitivity analysis of criteria weights is also conducted, as well as a comparative study, to demonstrate the effectiveness of the proposed method. It is essential to note that proper OSS-LMS package evaluation is crucial to avoid negative impacts on organizational performance. By addressing MCGDM issues and dealing with uncertain information, the c-WASPAS method presented in this study can assist clients in selecting the most appropriate OSS-LMS package from multiple alternatives. The findings of this study can benefit educational institutions and other organizations that rely on OSS-LMS packages to run their operations.

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Biographies

Deb Partha Pratim
https://orcid.org/0000-0001-7905-3911

P.P. Deb is an assistant professor and former head of the Department of Computer Science and Engineering Department at the Techno College of Engineering Agartala (TCEA), India. He has earned his M.Tech from Maulana Abul Kalam Azad University OF Technology (formerly West Bengal University of Technology), West Bengal, in 2013, and is currently pursuing his PhD from National Institute of Technology Agartala (NITA). He has served in various administrative positions at TCEA, including head of the Department, was in charge of Student Affairs, manager of Event Committee, member of the purchase committee. He was associated with variuos education institutes, including Convolution Educare, Techno International New Town (Formerly known as Techno India College of Technology) as an assistant professor. He is also a freelance software developer and project consultant of the software firm craftechgroup. He is an active associate member and junior convener of Computer Science and Engineering Div. of the Institution of Engineers (India) (IEI), Tripura State Centre. He has published different journals and participated in various national and international conferences. His current research interests include machine learning, artificial intelligence, time series prediction, digital image processing and MCDM.

Bhattacharya Diptendu
https://orcid.org/0000-0002-8981-710X

D. Bhattacharya received the BE degree from Malaviya National Institute of Technology (formerly MREC), Jaipur, Rajasthan, India, in 1988, also the M.E.Tel.E. (computer engineering) and PhD in engineering from Jadavpur University, Kolkata, India, in 1999 and 2016, respectively. He is currently an associate professor in the Department of Computer Science and Engineering, National Institute of Technology Agartala, India. He stood first class first position in order of merit in his M.E.Tel.E. Program. Dr. Bhattacharya was the head of the Department of Computer Science and Engineering, in National Institute of Technology, Agartala. He was also the winner of Weekly Nifty Prediction Contest organized by Personal Wealth Management Solutions Pvt. Ltd., Kolkata, India, in 2013. He has supervised 5 PhD theses. He has over 60 publications in international journals and conference proceedings. He is the author of book Time-Series Prediction and Applications: A Machine Intelligence Approach, Springer, 2017. Dr. Bhattacharya also authored 7 book chapters. He is popular among his students. Also, he supervised several B. Tech. and M. Tech. theses in his 32 years of teaching period in NIT, Agartala, India. His current research interests include artificial intelligence and soft computing, machine learning, IoT, optimization and precision agriculture, time-series prediction, computer vision, imaging, medical imaging, digital image and video processing, intelligent transportation system, intelligent vehicle, driving assistance system, online document image processing, natural language processing, pattern recognition etc.

Chatterjee Indranath
https://orcid.org/0000-0001-9242-8888

I. Chatterjee is working as a professor in the Department of Computer Engineering at Tongmyong University, Busan, South Korea. He received his PhD in computational neuroscience from the Department of Computer Science, University of Delhi, Delhi, India. His research areas include computational neuroscience, schizophrenia, medical imaging, fMRI, and machine learning. He has authored and edited 8 books on computer science and neuroscience published by renowned international publishers. To date, he has published numerous research papers in international journals and conferences. He is a recipient of various global awards on neuroscience. He is currently serving as a chief section editor of a few renowned international journals and serving as a member of the advisory board and editorial board of various international journals and Open-Science organizations worldwide. He is presently working on several projects of government & non-government organizations as PI/co-PI, related to medical imaging and machine learning for a broader societal impact, in collaboration with several universities globally. He is an active professional member of the Association of Computing Machinery (ACM, USA), Organization of Human Brain Mapping (OHBM, USA), Federations of European Neuroscience Society (FENS, Belgium), Association for Clinical Neurology and Mental Health (ACNM, India), and International Neuroinformatics Coordinating Facility (INCF, Sweden).

Chatterjee Prasenjit
https://orcid.org/0000-0002-7994-4252
p.chatterjee@mckvie.edu.in

P. Chatterjee is currently the dean (Research and Consultancy) at MCKV Institute of Engineering, West Bengal, India. He has authored over 120 research papers in various international journals and peer reviewed conferences. He has authored and edited more than 20 books on intelligent decision-making, supply chain management, optimization techniques, risk and sustainability modelling. He has received numerous awards including Best Track Paper Award, Outstanding Reviewer Award, Best Paper Award, Outstanding Researcher Award and University Gold Medal. Dr. Chatterjee is the editor-in-chief of Journal of Decision Analytics and Intelligent Computing. He has also been the guest editor of several special issues in different SCIE / Scopus / ESCI (Clarivate Analytics) indexed journals. He is the lead series editor of Disruptive Technologies and Digital Transformations for Society 5.0, Springer. He is also the lead series editor of “Smart and Intelligent Computing in Engineering”, Chapman and Hall / CRC Press, Founder and Lead Series Editor of “Concise Introductions to AI and Data Science”, Scrivener – Wiley; AAP Research Notes on Optimization and Decision Making Theories; Frontiers of Mechanical and Industrial Engineering, Apple Academic Press, co-published with CRC Press, Taylor and Francis Group and “River Publishers Series in Industrial Manufacturing and Systems Engineering”. Dr. Chatterjee is one of the developers of two multiple-criteria decision-making methods called Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI).

Zavadskas Edmundas Kazimieras
https://orcid.org/0000-0002-3201-949X

E. Zavadskas is a professor, head of the Department of Construction Technology and Management at Vilnius Gediminas Technical University, Vilnius, Lithuania, and a chief researcher at Research Institute of Smart Building Technologies. Prof. E. Zavadskas is a renowned developer of numerous MCDM techniques and his research interests include application of MCDM tools in solving engineering and management decision making problems, mainly in civil and structural engineering area.


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Keywords
intuitionistic fuzzy set cross entropy measure consensus based WASPAS OSS-LMS package selection

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