Identifying and Ranking Student Support Strategies in Higher Education Using Hybrid MCDM Technique and Assistant Professor,Department of H&S,Keshav Memorial Institute of Technology

Higher education institutions face complex challenges in identifying and implementing effective strategies that enhance student success and academic quality. This study proposes a hybrid Multi-Criteria Decision-Making (MCDM) approach integrating the Fuzzy Analytic Hierarchy Process (FAHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in order to estimate and rank student support mechanisms. The FAHP is used to get the relative weights of criteria under uncertainty, while TOPSIS is utilized to calculate the closeness coefficient for each alternative based on its proximity to the ideal solution. A case study is conducted to demonstrate the model’s applicability and versatility. Decision Matrix is created by survey of 400 students from various institutions in Andra Pradesh and the opinion of senior faculties having more that 15 years experience. The considered student support strategies are academic advising, career guidance, counselling, peer mentoring, and financial aid that are evaluated under criteria’s are taken as accessibility, effectiveness, satisfaction, cost efficiency, and impact on retention. The results expose the top-ranked strategies in their respective domains, emphasizing the importance of career-oriented support and interactive digital learning environments in fostering academic achievement. The least ranked strategy is financial aid, possibly due to limited accessibility and bureaucratic complexity. The visual analysis using bar and radar charts further illustrates the performance differences among alternatives, providing intuitive insights for academic administrators. The findings affirm that the hybrid FAHP– TOPSIS framework is a robust, flexible, and translucent decision-support tool capable of managing the inherent uncertainty and subjectivity of educational evaluation. This study contributes a replicable methodological model that can be extended to diverse decision contexts such as curriculum planning, institutional ranking, and quality assurance.