Mobile Tutoring for Situated Learning and Collaborative Learning in AIML Application Using QR-Code

Abstract

The aim of this paper is to illustrate a technique of integration between Tutor Bot and QR codes, used to label real objects during learning activities in direct educational contexts (egc. Situated learning and Authentic Learning). Tutor Bot knowledge base, structured in AIML (Artificial Intelligent Markup Language), is questioned in natural language using a mobile device (smart-phones, tablet, etc...) that, with a specific software decodes the instructions contained in a QR label placed on the real object observed by the learner. Through the information contained in the QR-Code Tutor Bot provides, in natural language, labeled object description and refers to further investigations: for example referring to multimedia resources related to the observed object. With the help of these tools, learners can expand their learning experience by interacting directly with a virtual tutor and real with the virtual world. With this technique, the activity of learning by doing, Situated Learning, Authentic Learning and Collaborative Learning, can be enhanced and virtualized by increasing the educational efficiency.