A Study of Ubiquitous Teaching Assistant (u-TA) Using Knowledge Retrieval, Adaptive Learning, and Location-based Service Techniques

• Main Authors: Lu-Hui Huang, 黃如慧
• Other Authors: Chyi-Ren Dow
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/80678953106297065299

博士 === 逢甲大學 === 資訊工程所 === 100 === Using software agents to assist students in virtual learning environments has become increasingly common for many experimental programs. However, without comprehensive consideration of constructing virtual teaching assistants, most of functions of virtual teaching assistants are bound and limited to virtual leaning environments. After building the learning systems, knowledge of virtual teaching assistants are usually no longer updated and cannot be accumulated through the interaction with the students. In addition, due to range of outdoor learning is wider than indoor learning, the teacher cannot take care all the students. Therefore, virtual teaching assistants should also consider providing location-based services to expand the scope of virtual assistant services. This work presents a framework to establish ubiquitous teaching assistant (u-TA). u-TA provides several system modules for different virtual learning environments. The proposed u-TA framework also supports the multi-modal user interfaces, such as Web-based and instant messenger-based interfaces. The proposed agent-based u-TA system has been enhanced social skills so that it can reduce the burden on teachers. u-TA can also learn knowledge from other agents by analyzing their dialogues. With the development of ubiquitous learning, u-TA should also consist of good mobility for guiding students and answering students’ questions on mobile handheld devices. Therefore, this work uses the u-TA framework to construct a location-based service (LBS) learning system to introduce the essence of courses to students and help them browse the content of the course resources on campus. Under the proposed framework, users can get helps from u-TA in virtual learning environments according their learning activities. Through analyzing Web logs or dialogue recordings of learning activities, u-TA can understand students’ learning behaviors and situations. The experiment results demonstrate that u-TA can assist students and share the TA’s workload in courses and has good communications ability and its user interfaces can increase interactions with students. We gave a case study for using the proposed system to promote the Service-Learning courses in Feng Chia University, Taiwan. The experimental results show that the proposed u-TA system can enhance the understanding of Service-Learning courses for students and encourage them to participate in these curricula.