Adaptive video techniques for informal learning support in workplace environments

Abstract

Learning at the workplace is largely informal and there is a high potential to make it more effective and efficient by means of technology, especially by using the power of multimedia. The main challenge is to find relevant information segments in a vast amount of multimedia resources for a particular objective, context and user. In this paper, we aim to bridge this gap using a personalized and adaptive video consumption strategy for professional communities. Our solution highlights relevant concepts within segments of video resources by means of collaborative semantic annotations, analyzes them based on the user’s learning objectives and recomposes them anew in a personalized way. As the preferred adaptation may be context dependent, the user has the opportunity to select a predefined adaptation strategy or to specify a new one easily. The approach uses a Web-based system that outputs a relevant mix of information from multiple videos, based on the user preferences and existing video annotations. The system is open source and uses an extendable approach based on micro-services. The performed evaluation investigated the usability and usefulness of the approach. It showed that effectiveness and especially efficiency of such informal learning could be indeed better with adaptive video techniques applied. On the other hand, collected ideas on how to improve the usability of the system show opportunities for its further improvements. These results suggest that personalization and adaptive techniques applied on video data are a good direction to proceed in facilitating informal learning in workplace environments.