A quantitative and model-driven approach to assessing higher education in the United States of America

University ranking or higher education assessment in general has been attracting more and more public attention over the years. However, the subjectivity-based evaluation index and indicator selections and weights that are widely adopted in most existing ranking systems have been called into question. In other words, the objectivity and impartiality of those rankings has been worrisome. To address these concerns, this paper presents a quantitative and model-driven approach to acquiring the evaluation index and indicator weights in the US News & World Report ranking system. Structural equation modelling will be applied to mine non-subjective weights from collected data. The proposed approach will be validated using two groups of United States universities, National Universities and Liberal Arts Colleges, classified by the US News & World Report. Managerial and administrative implications will also be explored. This study shows a very promising future because it opens a new venue for the scholars and practitioners in the higher education assessment field to develop a real-time, scalable and model-driven higher education ranking system.