出版社：The Japanese Society for Artificial Intelligence
摘要：The main topic addressed in this paper is how to help learners navigate in exploring hyperspace provided by existing web-based learning resources in which they can navigate Web pages in a self-directed way to learn the domain concepts/knowledge. Such self-directed navigation involves constructing knowledge from the contents embedded in the navigated pages, along what is called the navigation path, which has been demonstrated to enhance learning. Creation of a useful navigation path influences the knowledge construction process and plays an important role in self-directed learning in the hyperspace. On the other hand, learners often fail at creating a navigation path due to cognitive overload, which is caused by diverse cognitive efforts what may be viewed as meta-cognitive activities. Such meta-cognitive activities hold the key to success in self-directed learning. Our approach to this issue is to analyze the navigation planning tasks in order to design facilities that can more readily facilitate learners' planning activities. In this paper, we provide the learners with a navigation planning environment called Advanced Planning Assistant, which helps them plan a navigation path in an adaptive way before learning the hyperspace. This planning environment calls the learners' attention to establishing the navigation path prior to and separately from learning the hyperspace. We also report preliminary case study to evaluate the usefulness of the adaptive approach proposed. From the results of the case study, we have made sure that they are useful.
