Data literacy evaluation of undergraduate in business majors based on probabilistic linguistic integrated EDAS method

As the backbone of future society, the level of data literacy among undergraduates is crucial to the development of an information society. Hence, it is important to accurately assess and boost the data literacy of undergraduate students majoring in business. First, given the multi-index comprehensive evaluation of data literacy, a comprehensive system for evaluating the data literacy of undergraduates is established. Second, the integrated weights of the indices are determined using the probabilistic linguistic cross-entropy and Level Based Weight Assessment (LBWA) approach. Third, a probabilistic linguistic integrated Evaluation based on Distance from Average Solution (EDAS) method is proposed, and a case analysis of an undergraduate data literacy quality evaluation is conducted to demonstrate the proposed method. Finally, helpful recommendations are proposed to improve the development of data literacy among undergraduate business majors. This research not only enriches the evaluation indicator system for data literacy among undergraduate students in business majors but also provides scientific evaluation methods of reference value to researchers.