A Lecture Allocation Method Based on Multi-Leveled Value Model

Yoshihito Saito, T. Matsuo, T. Fujimoto
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Abstract

This paper describes the lecture allocation method and its support system for elective subjects. Students take a lecture for their career, for academical interest, and for assimilation of knowledge in a university. However, some students might take the lecture following the crowd and take the lecture as Mickey Mouse. To solve the problem, we propose a new multi-step lecture allocation method based on students’ preferences and university intentions. Our protocol consists of the three steps of negotiations and three types of allocations. (1) The university warns the students who have never take a certain compulsory subject yet. If the students answer they attend the lecture, the students are allocated to the lecture by priority. (2) The students inform the university of their reasons to take the lecture. The university allocates the lectures to the students based on their reasons. (3) They negotiate about the exchange of lectures to increase students’ utilities with each student. Our protocol realizes the high performance of allocation compared with brute force algorithm and reducing computational costs compared with optimizations.
基于多层次价值模型的课堂分配方法
本文介绍了选修课的课时分配方法及其支持系统。学生上课是为了他们的事业,为了学术兴趣,为了在大学里吸收知识。然而,有些学生可能会随大流,把讲座当成米老鼠。为了解决这一问题,我们提出了一种基于学生偏好和学校意向的多步骤课程分配方法。我们的议定书包括三个谈判步骤和三种分配方式。大学警告那些从未修过某门必修课的学生。如果学生回答他们参加了讲座,学生将按优先级分配到讲座。(2)学生告知学校他们参加讲座的原因。大学根据学生的理由来分配课程。(3)他们协商交换讲座,以增加学生与每个学生的效用。我们的协议实现了比暴力破解算法更高的分配性能和比优化算法更低的计算成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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