DESIGN AND IMPLEMENTATION OF EXAM-TIME-TABLE GENERATING SYSTEM
CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
In educational institutions, particularly in universities and colleges, the process of creating exam timetables is a complex and time-consuming task. The manual generation of exam timetables often leads to inefficiencies, conflicts, and inconsistencies, which can disrupt the smooth conduct of examinations and cause inconvenience to both students and faculty members. Recognizing these challenges, there is a growing demand for automated systems to streamline the process of generating exam timetables.
An undirected graph G is an ordered pair (V, E) where V is a set of nodes and E is a set of non-directed edges between nodes. Two nodes are said to be adjacent if there is an edge between them. The graph coloring is a well-known problem. Node coloring assigns colors to the nodes of the graph such that no two adjacent nodes have the same color. Edge coloring assigns colors to the edges of the graph such that no two adjacent edges have the same color. Two edges are said to be adjacent if they both share a node in common. General graph coloring algorithms are well known and have been extensively studied by researchers.
Exam scheduling is a challenging task that universities and colleges face several times every year.
The challenge is to schedule so many exams of courses in a limited, and usually short, period of time. An Exam schedule should avoid conflicts, in the sense that no two or more exams for the same student are scheduled at the same time. Part of the challenge is to achieve fairness for the students. A fair schedule does not schedule more than two exams, for example for a student on one day. In the meantime, a fair schedule does not leave a big gap between exams for the students. The exam scheduling problem is defined as follows: "We first represent the courses by nodes of a graph, where two nodes are adjacent if the two corresponding courses are registered by at least one student. Then, it is required to assign each course represented by a node a time slot, such that no two adjacent nodes have the same slot, in condition that a set of constraints imposed on the problem are also met." We solve this problem by using node graph coloring technique.
This study provides a mechanism for automatic exam-schedule generation that achieves fairness, and minimizes the exam period. As a result, this paper presents a graph-coloring-based algorithm for the exam scheduling application which achieves the objectives of fairness, accuracy, and optimal exam time period.
Numerous studies have considered the problem of exam scheduling. The main difference between various studies is the set of assumptions and constraints taken into consideration. Burke, Elliman and Weare, for example, followed a similar approach using graph coloring. However, in their algorithm, they addressed only the conflicts without any constraints. Moreover, the algorithm presented in does not eliminate conflicts, and only aims at minimizing conflicts. In this paper, we consider few but important assumptions and constraints, closely related to the general exam scheduling, and mainly driven from the real life requirements collected through the experience at various universities. Such assumptions and constraints are distinct from those present in more general graph coloring problems. We summarize the main assumptions and constraints as follows:
1. The number of exam periods per day (Time Slots (TS)) can be set by the user. TS depend on college/department specific constraints. For example, a university that uses a 2-hours exam period and begins the exam day at 8:00 am and finish at 8:00 pm, may set TS to 5.
2. The number of concurrent exam sessions or concurrency level (Np) depends on the number of available halls, and the availability of faculty to conduct the exams. Np is determined by the registrar’s office. This paper assumes that Np is a system parameter and the scheduling algorithm has been examined with several Np values.
3. A student shall not have more than (y) exams per day (fairness requirement), and is treated as a system tunable parameter.
4. A student shall not have a gap of more than (x) days between two successive exams, and this factor is to be determined by the college or department (another fairness requirement).
5. The schedule shall be done in the minimal possible period of time, i.e., minimize the number of exam slots and/or number of exam days. The exam time period is an outcome of the scheduling algorithm.
1.2 Statement of the Problem
The manual generation of exam timetables is prone to errors and inefficiencies, leading to conflicts and inconsistencies in scheduling. This often results in inconvenience for students and faculty members, as well as logistical challenges during examination periods.
1.3 Objectives of the Study
The main objective of this study is to determine the effectiveness of an automated exam timetable generating system in addressing the challenges associated with manual timetable generation. Specific objectives include:
i. To evaluate the impact of automated exam timetable generation on scheduling efficiency.
ii. ii. To determine the accuracy of the automated system in avoiding conflicts and inconsistencies in timetable scheduling.
iii. iii. To find out the level of user satisfaction with the automated exam timetable generating system.
1.4 Research Questions
i. What is the impact of automated exam timetable generation on scheduling efficiency?
ii. What is the accuracy of the automated system in avoiding conflicts and inconsistencies in timetable scheduling?
iii. How does user satisfaction with the automated exam timetable generating system compare to manual methods?
1.5 Research Hypotheses
Hypothesis I
H0: There is no significant impact of automated exam timetable generation on scheduling efficiency.
H1: There is a significant impact of automated exam timetable generation on scheduling efficiency.
Hypothesis II
H0: There is no significant difference in the accuracy of the automated system in avoiding conflicts and inconsistencies in timetable scheduling compared to manual methods.
H2: There is a significant difference in the accuracy of the automated system in avoiding conflicts and inconsistencies in timetable scheduling compared to manual methods.
Hypothesis III
H0: There is no significant difference in user satisfaction with the automated exam timetable generating system compared to manual methods.
H3: There is a significant difference in user satisfaction with the automated exam timetable generating system compared to manual methods.
1.6 Significance of the Study
The development and implementation of an automated exam timetable generating system have the potential to significantly improve the efficiency and accuracy of scheduling processes in educational institutions. This study aims to contribute to the existing body of knowledge by evaluating the effectiveness of such systems and providing insights into their impact on scheduling efficiency, accuracy, and user satisfaction.
1.7 Scope of the Study
This study focuses on the design and implementation of an exam timetable generating system for a specific educational institution. The scope includes the evaluation of the system's impact on scheduling efficiency, accuracy, and user satisfaction.
1.8 Limitations of the Study
One potential limitation of this study is the availability of data for evaluation, as the effectiveness of the automated system may depend on the quality and completeness of input data. Additionally, external factors such as changes in academic schedules or unexpected events may affect the results of the study.
1.9 Definition of Terms
Automated Exam Timetable Generating System: A computerized system designed to automatically generate exam timetables based on predefined constraints and parameters.
Scheduling Efficiency: The effectiveness and speed of the scheduling process in allocating exam slots and avoiding conflicts.
User Satisfaction: The degree to which users find the automated exam timetable generating system convenient, easy to use, and effective in meeting their needs.
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