Automatic Generation and Insertion of Assessment Items in Online Video Courses

Abstract

In this paper, we propose a prototype system for automatic generation and insertion of assessment items in online video courses. The proposed system analyzes text transcript of a requested video lecture to suggest self-assessment items in runtime through automatic discourse segmentation and question generation. To deal with the problem of question generation from noisy transcription, the system relies on semantically similar Wikipedia text segments. We base our study on a popular video lecture portal - National Programme on Technology Enhanced Learning (NPTEL). However, it can be adapted to other portals as well.