Using Bayesian Networks to Construct a Adaptive Learning Environment

• Main Authors: Chin-Chuan Hsieh, 謝錦泉
• Other Authors: Ho-Chuan Huang
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/33276936059458000273

碩士 === 國立高雄應用科技大學 === 資訊管理研究所碩士班 === 95 === Learning style is a major factor that affects learning performance of students. It is also noted that the learning diagnosis method is useful for instructors to evaluate the learning efficiency of student. Therefore, it becomes important how to automatically identify student’s learning style and diagnose student’s misconception in a web-based learning environment. The purpose of this research is to construct a learning diagnosis system that can identify automatically student’s learning preference and can evaluate student’s knowledge. In this study, Bayesian networks have been employed to make an inference about student’s learning styles based on student portfolio information. Besides, Bayesian inference mechanism can use the test results to identify potential misconception for student’s knowledge learning. With the support of Bayesian network mechanism, the system can deliver appropriate learning materials to assist students in constructing their own knowledge.