A FRAMEWORK FOR AUTOMATIC EXAM GENERATION BASED ON INTENDED LEARNING OUTCOMES

Abstract

Assessment plays important role in learning process in higher education institutions. However, poorly designed exams can fail to achieve the intended learning outcomes of a specific course, which can also have a bad impact on the programs and educational institutes. One of the possible solutions is to standardize the exams based on educational taxonomies. However, this is not an easy process for educators. With the recent technologies, the assessment approaches have been improved by automatically generating exams based on educational taxonomies. This paper presents a framework that allow educators to map questions to intended learning outcomes based on bloom’s taxonomy. Furthermore, it elaborates on the principles and requirements for generating exams automatically. It also report on a prototype implementation of an authoring tool for generating exams to evaluate the achievements of intended learning outcomes.