Generating computer-based advice in web-based distance education environments

There is an increasing demand for distance education to be implemented nowadays by most educational organizations. The Internet has become the medium for course delivery, and Web Course Management Systems (WCMS) are widely used to deploy distance courses which need to provide appropriate support to both students and instructors. The instructors play a central role in managing the course, and their success in dealing with reported problems in distance learning, such as students� isolation and disorientation in hyperspace, depends on the understanding the instructors have about what is happening in distance classes. Based on tracking data, most WCMS provide statistical information to help instructors monitor their students. However, there is a lack of automatic features to guide instructors by pointing at important situations and highlighting possible problems. Such features may help instructors, and reduce the workload and communication overhead needed for managing distance classes effectively. In this thesis, an approach is proposed where an artificial advisor is built to inform course instructors and facilitators about possible problems and needs of individuals and groups of students, as well as to suggest appropriate actions, when possible. A framework named TADV (Teacher ADVisor) has been developed to build fuzzy student, group, and class models based on the tracking data generated by WCMS. A taxonomy containing three main categories of advice related to the performance of individual students, groups of students, and the whole class is proposed, and an advice generator mechanism is developed. Important situations are highlighted to instructors and, when appropriate, possible actions are recommended. A prototype of TADV is implemented and integrated within an existing WCMS. An empirical evaluation of the prototype has been conducted in a Discrete Mathematics course at the Arab Academy for Science and Technology, Alexandria, Egypt. The evaluative study has shown that TADV provides practical and effective advice. It allows advice generation and informing of instructors, which, in turn, made it easy to send help and feedback to distance students. The instructors confirmed the appropriateness of the generated advice and appreciated the knowledge they gained about their students. The students appreciated the feedback received from the instructors, which was a result of TADV recommendations. The study showed better overall satisfaction and social aspects for the students who used TADV advising features.