aspg-21-1729-1791468692 20261008141132 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group International Journal of Neutrosophic Science IJNS 2692-6148 2690-6805 2023 20 4 Noura Metawa University of Sharjah, UAE Reneh Abokhoza Al Ain University, AbuDhabi, United Arab Emirates Ahmed Aziz Tashkent state university of Economics, Tashkent, Uzbekistan FinTech marketing education poses unique challenges that require new research directions. The constantly-evolving nature of the industry, coupled with the need to keep pace with technological advancements, demands an innovative approach to curriculum design and evaluation. Traditional education methods may not be sufficient to prepare students for careers in FinTech marketing, emphasizing the need for a multi-dimensional evaluation framework that considers business requirements, market trends, and customer needs. A Neutrosophic-Operational and Multi-Decision Analysis approach can provide a new direction for research, enabling educators to meet the evolving needs of the industry and better prepare students for successful careers in FinTech marketing. Throughout this article, we demonstrate a hybrid application of the Neutrosophic-AHP and the Multi-Criteria Decision Analysis technique for determining and assessing the most important characteristics of e-learning systems in the field of sustainability science education. Sustainability, scientific education, e-learning, and technological criterion are some of the most important to consider in order to reach this stated objective. The participative neutrosophic AHP method examined sixteen sub-criteria in terms of the value and calculation of coefficients within the framework of impact and evaluation. The most crucial factors for the ultimate choice issue are gathered. Therefore, techniques such as neutrosophic-operational and multi-decision analysis, as well as expert surveys, may be used to identify the most important criteria for e-learning in the field of sustainability science, which can then be employed to develop adaptable and relevant decision features. 2023 197 209 1729 https://creativecommons.org/licenses/by/4.0/ 10.54216/IJNS.200416 https://www.americaspg.com/journal/21/article/1729 https://www.americaspg.com/storage/51682684952.pdf