Balancing Academic Curriculum Problem Solution: A Discrete Firefly-Based Approach

Q3 Social Sciences Education Research International Pub Date : 2023-02-09 DOI:10.1155/2023/4300472
Avita Katal, Vijay K. Singh, T. Choudhury, F. Imran, Md. Sabbir Hossain
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Abstract

The difficulty of allocating a balanced educational syllabus to academic periods of a curriculum, also known as curriculum balancing, has long been a source of consternation for any institution of higher education attempting to connect learners and teachers. The balanced academic curriculum challenge entails assigning courses to academic times while adhering to all load restrictions and prerequisite requirements. The balanced academic curriculum problem (BACP) includes assigning subjects to class hours that fulfill standards even while managing students’ burden in terms of credits, course load, and perquisites that includes subjects covered in the previous semesters/periods. The number of credits every semester corresponds to the academic load. As a result, educational frameworks must be “balanced,” which means the credits for each period should be equivalent in order for students to bear minimum work. As a result, it is desirable to reduce this cost by developing a study plan that employs an algorithm that conducts this work automatically. Using an optimization method, this article provides a solution to the challenge of curricula balancing based on the discrete firefly algorithm (DFA). In research, FA has already been used to solve the BACP problem. However, the basic FA is modified to DFA with a local search mechanism inbuilt that helps to reach optimum solution in less number of iterations. A series of tests on standard and real data instances are done to check the efficiency of the suggested approach, with the objective of producing a platform that would simplify the procedure of building a curriculum system at institutions of higher learning. The results show that the proposed solution obtained a rather rapid solution and hit the recognized optimum in most of the iterations.
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平衡学术课程问题解决:基于离散萤火虫的方法
对于任何试图将学习者和教师联系起来的高等教育机构来说,分配一个均衡的教学大纲的困难,也被称为课程平衡,一直是一个令人困惑的问题。平衡的学术课程挑战需要在遵守所有负荷限制和先决条件要求的同时,将课程分配到学习时间。平衡学术课程问题(BACP)包括分配符合标准的课程时数,同时管理学生在学分、课程负担和额外费用方面的负担,包括前几个学期/学期的课程。每学期的学分数与学业负荷相对应。因此,教育框架必须是“平衡的”,这意味着每个学期的学分应该是相等的,以便学生承担最少的工作。因此,我们希望通过开发一种学习计划来减少这种成本,该计划采用一种自动进行这项工作的算法。本文采用优化方法,提出了一种基于离散萤火虫算法(DFA)的课程平衡难题解决方案。在研究中,FA已经被用于解决BACP问题。然而,基本FA被修改为DFA,内置了一个局部搜索机制,有助于在更少的迭代次数中获得最优解。对标准和真实数据实例进行了一系列测试,以检验所建议方法的效率,目的是建立一个平台,简化高等院校建立课程系统的程序。结果表明,该方法在大多数迭代中都能快速求解并达到识别的最优解。
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来源期刊
Education Research International
Education Research International EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
2.70
自引率
0.00%
发文量
212
审稿时长
21 weeks
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