Constructing Problem-Based Learning Activities Using Self-assessment System

Abstract

Along with the information and communication technology getting more mature, the e-learning becomes more popular and more diverse. Many researches have pay much effort on exploiting the data-mining techniques to make user-learning more efficient. In this study, we mainly develop an experimented self-directed e-learning system, which tries to adopt adaptive testing based on the experts’ knowledge and experiences to support problem-based learning activities. Within the item bank construction, we invite domain experts to assist the collection and creation of examination items and classification. Particularly, on the setting of item keywords, it is one of the most important processes for learners to easily discover related works as well as to easily share their collaborative learning activities. Additionally, after each evaluation, learners can not only follow the suggestions from the assessment system to find out the related materials which are collaboratively filtered by precursors’ learning activities, but they also can easily contribute their learning modes in the same ways. We hope such collaborative self-assessment platform, which integrates the self-directed assessment system and the learning activity-based material recommendation system, make learners easier to share their learning experiences and then, improve the efficiency of self-directed learning.