Paperless Master Timetable Scheduling System

Daniel, Paul Godwin; Maruf, Alimi Olasunkanmi; Modi, Bala

doi:10.30845/ijast.v8n2a7

Cited by 6 publications

(5 citation statements)

References 4 publications

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“…It can be prepared manually or automatically. [2], [3], [4] The preparation process itself is influenced by a number of factors such as the availability of a certain resource, a fixed period of time (academic year, summer/winter season, etc.) as well as a number of initial parameters (number of students, number of classrooms available, etc.).…”

Section: Study Timetablementioning

confidence: 99%

A Mathematical Model for Rationality in Timetable Planning

Kostadinova¹,

Totev²,

Ivanov³

2023

TEM Journal

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The preparation of a study timetable (or schedule) depends on the school or university for which it is made and on the specific work practices applied in this educational institution. The preparation of a school timetable in a school or university aims to plan for the conduct of classes in certain academic disciplines for a certain period of time, while optimally engaging the classrooms and professors available for the relevant period. The aim of this paper is to provide a mathematical model for rationality in planning a study timetable. This mean to make forecast on whether the accepted number of students, organised in groups, could be instructed during defined period of time in the available classrooms in the educational institution. The developed model aims to make better use of available classrooms and places for students in them. Calculating a rationality ratio will give the educational institution an idea of the:  Need for more classrooms;  Need to extend the study period (number of days for the planned semester)  Need for more optimal planning of the study timetable and better use to the rooms. The prepared model also includes a coefficient of specific rationality, in case the educational institution has classrooms of different capacities - for lectures and practical exercises. The developed mathematical model can be useful to higher education institutions for the purpose of planning their educational activity and it can be applied before the actual process of planning a study schedule. The data used and calculations results serve as the basis for an in-depth analysis related to the requirements for the educational process and the opportunities provided by the educational institution.

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Section: Study Timetablementioning

confidence: 99%

A Mathematical Model for Rationality in Timetable Planning

Kostadinova¹,

Totev²,

Ivanov³

2023

TEM Journal

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“…The main open challenge in automated class scheduling is the integration of "soft restrictions" into the optimization algorithm. For example, conditions related to the number of students in each room [17] or non-usual break periods [18]. To address this problem, many different scheduling and optimization techniques have been applied to class scheduling: from Particle Swarm Optimization (PSO) [19] and integer programming [20], to hyperheuristics [21], fix-and-optimize metaheuristic [22] and several different algorithms such as the Great deluge algorithm [22] or genetic algorithms [23].…”

Section: State Of the Artmentioning

confidence: 99%

Automated Activity Scheduling Tools for Improving Learning and Evaluation of Cybersecurity Competencies in Computer Engineering Courses

Bordel

Alcarria

Robles

2023

Int. J. Emerg. Technol. Learn.

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In the last ten years, many different innovative learning methodologies have been proposed for engineering education. In those new approaches, students learning, and evaluation are usually supported by a catalogue of creative activities, practices, and presentations which may be very numerous if competencies to be acquired are heterogeneous and must cover a large knowledge area, such as in cybersecurity courses. In addition, when a high number of students are enrolled in the course, deadlines must be strict, to enable professors to evaluate all students and activities properly and on time. Due to this requiring schedule, students often cannot work all competencies with the expected depth, and their learning decreases. New instruments are needed to facilitate the learning of the students and the evaluation process are needed. Therefore, in this paper we proposed a new automated scheduling tool, based on graph theory, to fill this gap. The tool employs graph coloring algorithms to calculate all possible schedules for evaluation activities. Students may freely choose the schedule that best fits their personal situation, learning progress, background, etc. using a web portal where all solutions from the coloring algorithm are displayed. This tool was deployed in the Computer Engineering degree at Universidad Politécnica de Madrid, Spain. A pilot experience was conducted for three years (2020-2022) in the context of a cybersecurity course to analyze how this new tool improves the learning and the evaluation process of students. Results show both academic results and the students’ and professor’ satisfaction improve in a significant manner.

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“…journal.ump.edu.my/mekatronika ◄ Parameters and constraints serve as fundamental elements within a scheduling algorithm, as noted in reference [7]. It is crucial to account for all these parameters and constraints, and this represents the most challenging aspect of creating a schedule without conflicts, as highlighted in references [8] through [10]. The parameters within the schedule encompass students, time slots, classroom venues, and the assignment of two evaluators to evaluate a single student in a room concurrently.…”

Section: Problem Descriptionmentioning

confidence: 99%

Efficiency and Accuracy of Scheduling Algorithms for Final Year Project Evaluation Management System

Loo,

Toh,

Ab. Nasir

et al. 2023

MEKATRONIKA

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Scheduling algorithms play a crucial role in optimizing the efficiency and precision of scheduling tasks, finding applications across various domains to enhance work productivity, reduce costs, and save time. This research paper conducts a comparative analysis of three algorithms: genetic algorithm, hill climbing algorithm, and particle swarm optimization algorithm, with a focus on evaluating their performance in scheduling presentations. The primary goal of this study is to assess the effectiveness of these algorithms and identify the most efficient one for handling presentation scheduling tasks, thereby minimizing the system's response time for generating schedules. The research takes into account various constraints, including evaluator availability, student and evaluator affiliations within research groups, and student-evaluator relationships where a student cannot be supervised by one of the evaluators. Considering these critical parameters and constraints, the algorithm assigns presentation slots, venues, and two evaluators to each student without encountering scheduling conflicts, ultimately producing a schedule based on the allocated slots for both students and evaluators.

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Paperless Master Timetable Scheduling System

Cited by 6 publications

References 4 publications

A Mathematical Model for Rationality in Timetable Planning

A Mathematical Model for Rationality in Timetable Planning

Automated Activity Scheduling Tools for Improving Learning and Evaluation of Cybersecurity Competencies in Computer Engineering Courses

Efficiency and Accuracy of Scheduling Algorithms for Final Year Project Evaluation Management System

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