This study scientifically assessed digital education resources to determine how to develop these materials effectively. Data were obtained from the Smart Education Platform of China for higher education. Particularly, this research examined online reviews from learners who have used resources in various subjects, including music and art, humanities and social sciences, education and teaching, medical and health, computer science, and economic management. Then, topic modeling was applied to identify the important factors that influence the quality of digital education resources. Results show that content organization and language expression are the most pertinent dimensions, followed by knowledge explanation, teaching materials, and learning evaluation. Meanwhile, resource adaptability, teaching media, strategies, interaction, expansion of resources, learning experience, learning effectiveness, resource renewal, and teacher characteristics have a relatively limited influence on resource quality. This study also employed opinion mining, which revealed that digital education resources have the highest outcomes in the areas of learning effectiveness, teaching strategies, teacher characteristics, and resource adaptability. Meanwhile, these resources have the poorest results in learning evaluation, teaching media, and resource renewal. Furthermore, results revealed that music and art resources have the best quality among all types of digital education resources. By contrast, resources for computer science and economic management have relatively poor quality. This study ultimately presents a viable approach for evaluating digital education resources, which can then be used to offer practical guidance on raising the quality of digital education resources across various subjects.