Expanding Annotation to Mixed-Media Types in a Large-Scale Social Annotation Platform

Abstract

In recent years, social annotation systems have become a popular and effective tool for hosting collaborative discussions on assigned readings. One such tool created by our lab is NB. Over the last twelve years, hundreds of instructors have incorporated NB within their classes, with over 50,000 students leaving millions of annotations [1]. While feedback for NB has mostly been positive, one major limitation is its difficulty in annotating documents with nested media types. As multimodal forms of learning beyond just text are becoming increasingly common in educational assignments, having the ability to annotate beyond simple text documents would greatly increase the utility of NB in the modern classroom. This work seeks to remedy this issue by expanding the types of documents NB can successfully annotate, specifically focusing on three mixed-media issue types: independently moving text components, image annotation, and video annotation. We will explore the design space of possible implementation strategies for these features and discuss the specific design decisions that were made when adding them to NB. We hope that by increasing the types of documents NB can annotate, we will better fulfill its goal of enhancing student engagement and learning.