Grade Inflation: A Crisis in College Education Book

Grade inflation runs rampant at most colleges and universities, but faculty and administrators are seemingly unwilling to face the problem. This book explains why, exposing many of the misconceptions surrounding college grading. Based on historical research and the results of a year-long, on-line course evaluation experiment conducted at Duke University during the 1998-1999 academic year, the effects of student grading on various educational processes, and their subsequent impact on student and faculty behavior, is examined. Principal conclusions of this investigation are that instructors' grading practices have a significant influence on end-of-course teaching evaluations, and that student expectations of grading practices play an important role in the courses that students decide to take. The latter effect has a serious impact on course enrollments in the natural sciences and mathematics, while the combination of both mean that faculty have an incentive to award high grades, and students have an incentive to choose courses with faculty who do. Grade inflation is the natural consequence of this incentive system. Material contained in this book is essential reading for anyone involved in efforts to reform our postsecondary educational system, or for those who simply wish to survive and prosper in it. Valen Johnson is a Professor of Biostatistics at the University of Michigan. Prior to accepting an appointment in Ann Arbor, he was a Professor of Statistics and Decision Sciences at Duke University, where data for this book was collected. He is a Fellow of the American Statistical Association, co-author of the graduate statistical textbook, Ordinal Data Modeling, has served as an associate editor for both the Journal of the American Statistical Association and IEEE Transactions on Medical Imaging}, and is a past Treasurer of the International Society for Bayesian Analysis. His research interests include ordinal and rank data analysis, statistical image modeling, convergence diagnostics for Markov chain Monte Carlo simulation algorithms, and educational assessement.Read More