Interactive Decision Support System for Planned Student Scheduling and Incremental Changes in Large Scale Timetabling

Abstract

A student joins an institution to earn some qualification. For this purpose, he/she has to successfully complete a set of courses in a span of few terms. Some of the students fail in some of the courses studied in a term. Such courses are called backlog courses. Backlog courses have to be taken up in any of the successive terms possible only if these are offered to junior class students in one or more sections. The planning needed to help students in deciding which courses can be taken with which of the section of junior class students, forms the core of present thesis. Besides this, the thesis also covers incremental changes to be made in a working time table once the whole process has stabilized. This thesis consists of six chapters. Chapter One is introductory in nature. In this chapter, we briefly discuss the issues of backlog courses while preparing timetable. Two approaches generally used to handle this problem and some important terminologies are also discussed in this chapter. A brief survey of the literature available on the subject, and summary of the work presented in the succeeding chapters of the thesis, also appears in this chapter. The second chapter describes the model for planning of student scheduling. Planning of student scheduling involves the linking of courses that the students will be attending with students of junior classes while they are free. This scenario is solved by a method developed to find out backlog courses which can be pooled together in same time slot along with keeping free the sections of students where regular courses are held. This process is termed as planning for student scheduling whose output can be considered as a set of constraints to be used in building the time table. The Hungarian method of assignment model has been repeatedly used to form links further required as an input for scheduling of the timetable. A core model has been designed using Dynamic Programming approach spread across five stages where each stage is referring to one year of study. Fifth stage and year refers to students who have studied all four year of programmes but are still having backlog courses at the end of it. In this chapter, the links are termed across years where each year has only one group of students studying together in single section. Third chapter describes two models for real life implementation of planning of student scheduling. The assumptions and methodology used for arriving at data-sets is emphasized. Planning of student scheduling is done using repeated use of assignment problem solution and heuristics. The implementation details have been provided for testing the models developed for decision support system. The algorithms for implementing two variants of this model have been described in detail. Results of implementations are evalv uated for their efficiency and achievement of objective. Planning of student scheduling model is judged against the current system in use. Results have been demonstrated in this regard.The above generated inputs can be used to build the time table. Fourth chapter describes the model for interactive student scheduling. Students can easily get registered in courses planned to be backlog courses. However, the courses which are not planned this way can still be registered as backlog courses but this becomes a tedious work to scroll time table of whole institute to complete this search. One tool has been made which searches and confirms the course section combinations which are clash free to search in an already built time table. The students can get registered in combinations searched in this way for combination of back log and regular courses. This is termed as registration process. Interactive student scheduling provides a user interface that helps in identifying clash-free set of course sections to be registered based on the constructed time-table. Two models have been designed for searching clash free combinations of course-sections. These two models provide a working process that helps in decision making process at the time of registration by a student. As this is at present done manually and no other methods are available so it is not possible to measure the new models against anything. So both are tested against each other as they solve the same problem differently. Fifth chapter describes the model for Incremental Changes in Large Scale Time-Tabling. Students start studying as per their student registrations, and there is a need to make change in time table, one search tool has been created which can approve or disapprove a time table change request while protecting the combinations of student registrations already made. This system will ensure the time tables of individual students are still clash free. This is termed as incremental changes in large scale timetabling. Incremental Changes in Large-Scale Timetabling decides whether the suggested change can be made without affecting the clash-free timetables of students who have earlier registered in any of the courses in which change is sought. Next, the implementation details are provided for testing the models developed for decision support system. The algorithms for implementing various scenarios for this model are described. The user interface for implementation is explained along with the explanation of terminology used. Incremental Changes in Large Scale Timetabling uses heuristics to find the feasibility of changes requested. Results of implementations are evaluated for their efficiency. These models are judged by the variety of options provided by the decision support system to achieve the goals. These models provide a working process that helps in decision making process at the time of changes to be made in time table post registration. As this is at present done manually so it is not possible to measure the new models against anything. These vi models add to Quality of Service provided to the users for making changes possible in final time table. The last and sixth chapter summarizes the contents of thesis and discusses the contributions as well as limitations of the present research. With summary of contributions, the chapter also envisions the future research work.