Automatic Grading of Student-Specific Exercises in Large Groups of the Subject Theory of Machines and Mechanisms

Abstract

This study establishes an already defined and tested method to grade exercises of kinematics and dynamics within the course entitled “Theory of Machines and Mechanisms” of the Industrial Technologies Engineering Degree at the Seville School of Engineering (Spain). Particular emphasis is made on the automation of grading and personalization of the exercises, due to the large number of students enrolled in this course. The former is made through a teaching platform available at the University of Seville and called Doctus, whilst the latter is achieved by defining the input data of the exercises and the requested results as a function of the digits of the student’s ID. The students must face and solve a personalized problem by their own with the knowledge and competences acquired during the academic course. This paper describes the exercises and the tools used to grade them and shows the satisfactory results obtained with these exercises after three academic courses.