COMPUTATIONAL APPROACH FOR MOBILE IMAGE-BASED LANGUAGE LEARNING

In this paper authors present results of designing image-based language learning (IBLL) applications as part of computer assisted learning activities in mobile environment. For integrating a mobile device to learning process the proposed computational approach provides remote access to multimedia documents that implies image acquisition, processing, recognition and retrieval. Some algorithms have been proposed for image-based symbols indexing and recognition, particularly for interpretation of Japanese kanji and Mayan glyphs on mobile devices with limited resources and restricted networking capabilities. This approach can suggest ways of studying and organizing resources, provides long-term guidance on developing skills and supports experiential learning. It has been tested in order to evaluate processing speed and recognition grade for interpretation of image-based characters on commercial cell phones and PDAs. The obtained results demonstrated the effectiveness of the developed approach, its high processing speed and acceptable symbol recognition precision. Our proposal could be considered as alternative way for development of computer-based learning assistants in wireless environment which may support experiential learning solutions and recommendations for image-based language learning.