INNOVATIVE METHOD FOR GRADUATE ATTRIBUTE ASSESSMENT IN LARGE CLASSES

Abstract

Assessing graduate attributes in large classes is a time consuming task. The assessment requires a carefully designed random sampling that ensures the sample is representative of all students in the class. In addition, the assessment becomes more difficult when soft-skill graduate attributes are involved. The purpose of this paper is to present an efficient method for assessing graduate attributes in large classes without sampling. The proposed method involves defining an indicator (learning objective) by knowledge elements (topics) that the student should know or by interaction elements in a case study that represent the principles related to the indicator. Multiple-choice questions are then developed for the knowledge or interaction elements and processed using scantron sheets. The method involves a weighted-score procedure and performance scales for determining class performance. Application of the method for assessing two graduate attributes (lifelong learning and professionalism) in a fourth-year common engineering course is illustrated in this paper. The results show that class performance is sensitive to the weights assigned to the questions and therefore these weights should be carefully established by the instructors. The proposed method has shown to be useful in identifying the indicators and the specific topics within the indicator that need improvements.