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Autonomous tagging-assisted lecturing using google glass and other wearable devices

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Autonomous tagging-assisted lecturing using google glass and other wearable devices

Abstract

The introduction of wearable devices in the educational environment enables using novel technology-based assistance during the lecturing process. In the academic environment, the use of hands-free mobile devices is preferred in order to be able to interact with the students without needing to hold a device. In this work we propose using head-mounted displays such as Google Glass or other wearable devices to perform automatic tagging of the contents written by the teacher in the blackboard or codes included in the students’ tasks. The system autonomously detects equations and specific chalk writing marks and can be configured to send automatically extra contents to previously registered alumni personal devices. The use of Google Glass or other wearable devices in the classroom enables a whole new range of intelligent applications. The lecturing professor can collect important data regarding the student knowledge building and using this information improve the learning efficiency. A compatible smartwatch is integrated in this scenario to change slides automatically while speaking, enabling the teacher liberty of movement around the classroom. In this way, the teacher controls the timing needed for each concept during the exposition and also the time consumed in each activity proposed during the classroom lesson. The prototype work has been tested in the seminar of Energy Efficiency and New Generation Access Optical Networks of the Master in Technology, Systems and Communication Networks of the Universitat Politècnica de València (UPV), Spain. The real-time updates and notifications available in the wearable device prototype employed in this work permit the continuous interaction within the classroom without interrupting the lecture. The results from the autonomously sent tests and exercises are presented to the lecturer in the Google Glass display as soon as the student finishes. Using the proposed autonomous tagging-assisted lecturing system enables a quick perception of the rate of success in the alumni knowledge building process.