Extending e-books with contextual knowledge recommenders by analyzing personal portfolio and annotation to help learners solve problems in time

摘要

When students encounter problems during learning process, they need support on time. Nevertheless, most references or answers are distributed in different books or Web content. Therefore, students need to break their reading process and spend much time to search answers from different reference books. Otherwise, increased frustration and confusion will decrease the students' learning performance. This research proposed a Web-based learning environment with contextual knowledge and expert recommending mechanisms for students' problem solving when they are reading e-books. A Web dictionary and a library of examples were constructed beforehand to support students referring. A Q&A forum was also constructed for students consulting directly. Classmates will be notified as mentors to answer peers' questions if those articles in forum could not solve students' questions. Experiment results show that students prefer referring knowledge and joining discussion in our system then the same system just without those functions. Our mechanism also shortened the response time about student's questions posting in forum.