Generation of assessment questions from textbooks enriched with knowledge models

Abstract

Augmenting digital textbooks with assessment material improves their effectiveness as learning tools. It can be a laborious task requiring considerable amount of time and expertise. This paper presents an automated assessment generation tool that works as a component of the Intextbooks platform. Intextbooks extracts fine-grained knowledge models from PDF textbooks and converts them into semantically annotated learning resources. With the help of the developed assessment components, these textbooks become interactive educational tools capable to assess students' knowledge of relevant concepts. The results of an expert-based pilot evaluation show that generated questions are properly worded and have a good range in term of difficulty. From the point of assessment value, some generated questions types fall behind manually constructed assessment, while others obtain comparable results.