In core engineering courses, instructors administer multiple examinations as major assessments of students' learning. When a student is unable to take an exam, the instructor must estimate the missing exam score in order to calculate the student's course grade. Using exam score data from multiple offerings of two large engineering courses, we compared the accuracy of several methods to estimate an exam score, including linear regression methods. The standard error of regression of the ordinary least squares (OLS) regression model was consistently about 0.5. For final exam scores, the standard errors of linear models with equal weights were nearly the same as the standard errors of the OLS regression models. For other exam scores, the equal weight model was somewhat less accurate. The results of this study provide practical guidance to instructors who need to estimate missing exam scores.
['Michael C. Loui', 'Athena Lin']
How should we estimate a missing exam score