This paper describes a design and implementation of object-oriented architecture for a learner-adaptive self-learning environment. The design goal of this architecture is to provide a flexible self-learning environment that ensures both function extensibility and content reusability. A prototype system was designed and implemented to investigate the feasibility of the proposed architecture and to identify the core behavior and interaction schema of courseware objects. Successful implementation of fully functional SCORM 2004 execution system into the proposed architecture indicates its practical capability as a common platform for various learner-adaptive functionalities.

This study proposes a sightseeing and learning navigation mobile system using adaptive testing. The unique features of the system are as follows: (1) Navigation function guides a user to sightseeing spots with GPS and compass. (2) Adaptive testing function provides items concerning sightseeing spots and helps to focus a user’s viewpoint to the tourist attractions points. The system predicts the user’s knowledge level about the tourist attractions, and presents the test items that maximize the amount of information based on Item Response Theory (IRT). This study shows that the tourist are interest in knowledge for which item has a high IRT information value. Evaluation experiments confirm the effectiveness of the system.