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The purpose of this paper is to present a user interface for web lectures for engaging with other users while working with video based learning content. The application allows its users to ask questions about the content and to get answers from those users that currently online are more familiar with it. The filtering is based on the evaluation of past user interaction data in time‐based media.

The work is implemented as a prototype application in the context of the Opencast Matterhorn project – an open source based project for producing, managing and distributing academic video content. The application compares users viewing behavior and allows communication with others that are good candidates to answer questions.

Different filtering approaches for identifying suitable candidates are being discussed that foster past interactions in time‐based media.

The paper shows that web lectures can benefit from user awareness ideas and presents examples of how learners can benefit from the knowledge of other users who are working with the same video based content.

User awareness has become an important feature in today's Web 2.0 experience. The paper discusses different user awareness models and explains how they can be adapted to time‐based video content. The presented work is available as a plug‐in for the Opencast Matterhorn project.