Using information on unconstrained student demand to improve university course schedules

Using Course and Student Profiles to Improve Student Success

Student Learning Experience with an Industry Certification Course at University

This is an analysis of the computer generated feedback from an industry certification course, as taught as part of a university unit. A method for extracting useful information from the available course evaluation data is proposed, and the method is shown to be effective and reasonable. Conclusions for the particular unit are drawn. In particular it is shown that the unit was successful in givi...

Student Dropout Risk Assessment in Undergraduate Course at Residential University

Student dropout prediction is an indispensable for numerous intelligent systems to measure the education system and success rate of any university as well as throughout the university in the world. Therefore, it becomes essential to develop efficient methods for prediction of the students at risk of dropping out, enabling the adoption of proactive process to minimize the situation. Thus, this r...

On the Design of Efficient Video-on-Demand Broadcast Schedules

In order to address the scalability problems of Video– on–Demand systems, several periodic broadcast schemes have been proposed that partition a video into segments and repetitively broadcast each segment on a separate channel. A new scheme is presented for the bandwidth–efficient periodic broadcast of video. The proposed scheme determines the segment sizes and their corresponding channel bandw...

Using Course Constraints in Simulating Student Populations

Distance learning universities usually afford their students the flexibility to advance their studies at their own pace. This can lead to a considerable fluctuation of student populations within a programme’s courses. The evolution of the student population may be an important factor in determining the academic viability of a programme as well as the resources that have to be budgeted and admin...