###### Abstract
[PERSON] [25] developed SecondLife, a web-based virtual reality tool designed for civil and environmental engineering students. This tool highlights the importance of students developing their employability skills from the beginning of the academic year, alongside their university instruction, thereby enhancing the university's engagement with industry. [PERSON] and [PERSON] [26] employed SPSS statistical tests to predict students' performance in a three-year course on creating Water Resource Engineering (WRE) systems at the University of South Australia. They examined the relationship between students' online engagement and their academic success. The Multi-Criteria Decision-Making (MCDM) approach is a widely used method for decision-making across various fields. One of the MCDM techniques, the Analytical Hierarchy Process (AHP), is a powerful and intuitive tool that involves pairwise comparisons of alternatives based on expert assessments. This approach helps to separate and distinguish the elements of a problem by assigning weights to them [27; 28; 29; 30]. The AHP technique has been utilized by [PERSON] et al. [31] to assess the relative importance of qualitative factors influencing student satisfaction. According to existing studies [32; 33], the increasing use of the AHP method in educational settings has led to the prioritization of more relevant parameters aimed at enhancing both the quantitative and qualitative aspects of educational institutions and research centers. While researchers also apply alternative methods such as FUCOM, BWM, DIBR, and LBWA, their use is often constrained by specific objectives and limitations. In contrast, this study opted for the AHP method due to its widespread popularity among researchers [34; 35; 36; 37; 38]. There are several computational methods available for multi-criteria decision-making, each with its own advantages and limitations. For example, the VIKOR method is commonly used in decision-making processes that employ compromise programming. This method is particularly useful when the decision-maker faces challenges in determining the relative importance of criteria, whether proportional or non-proportional. In such scenarios, the VIKOR method helps identify a solution that takes into account multiple criteria simultaneously [39]. Another method, called MABAC, has been proposed specifically for ranking research alternatives. It determines rankings based on the distance from the geometric mean of the available options. However, it is important to note that the applicability of this method is limited to certain scenarios, and the resulting rankings may not provide sufficient value or accuracy for all types of problems [40]. MAIRCA is another MCDM technique that generates rankings for different options after performing the necessary computations. The inputs for this method include the decision matrix, criterion weights, and types of criteria. Key concepts such as gap, actual weight, and theoretical weight are integrated into the method and influence the final ranking. Notably, the best option in this technique is determined by the one with the smallest gap. It can be said that this method follows a comprehensive process to reach a solution [40]. Among the newer ranking methods for multi-criteria decision-making problems is the MARCOS method. Similar to the TOPSIS method, alternatives are ranked by constructing a decision matrix. However, the MARCOS method alone cannot calculate criterion weights and is typically used in conjunction with other techniques, such as AHP [41; 42]. In this particular study, the TOPSIS method was employed. The use of the TOPSIS method allows for the identification of the best possible solutions within the range of problem criteria, while properly accounting for the importance of each criterion [43; 44]. The advantages of this method include its ability to handle both positive and negative criteria, accommodate both quantitative and qualitative criteria, and convert qualitative criteria into quantitative measures.