This paper aims to develop and validate a Supervised NLP-based method for evaluating the alignment between academic management and student educational awareness. As a methodological framework, the study utilizes a model constructed based on students’ educational perceptions as supervised training data. The study derives inference and correction models by comparing these with official university documents, thereby establishing a novel framework for assessing instructional alignment. A numerical experiment involving clustered private women’s universities in Japan is conducted to verify the validity of this evaluation approach. The results demonstrate a discrepancy: instructional management emphasizes “international learning,” while current students place the highest importance on “obtaining national qualifications.” This contrast confirms the utility of the proposed method. In addition, the analysis reveals a diminishing emphasis on close faculty-student relationships, while extracurricular activities, including student clubs, are consistently valued by both institutions and students.