Comprehensive Analysis Using 2-tuple Linguistic Neutrosophic MADM with Core Competencies Evaluation of Track and Field Students in Sports Colleges

The core competencies evaluation of track and field students in sports colleges holds significant importance. It not only helps assess students' overall abilities in track and field, such as physical fitness, athletic skills, psychological quality, and social responsibility, but also provides a scientific basis for personalized teaching and training. Through this evaluation, students' strengths and weaknesses can be identified, allowing for the optimization of training strategies to improve their athletic performance and holistic development. Additionally, this evaluation aids in cultivating students' teamwork, psychological resilience, and sense of social responsibility, ensuring that they are more competitive and adaptable in their future sports careers, thereby promoting their long-term development. The core competencies evaluation of track and field students in sports colleges is regarded as a multi-attribute decision-making (MADM) problem. In this study, we integrated the geometric Heronian mean (GHM) approach and prioritized aggregation (PA) with 2-tuple linguistic neutrosophic numbers (2TLNNs) to develop the generalized 2-tuple linguistic neutrosophic numbers prioritized GHM (G2TLNPGHM) approach. Additionally, we explored several key properties of the proposed approach. The G2TLNPGHM approach was then applied to address MADM problems under the framework of 2TLNNs. To demonstrate its practical application, the method was used as an example for evaluating the core competencies of track and field students in sports colleges. Lastly, a comprehensive comparative analysis was conducted to examine the effects of varying parameters on the results.