Analyzing the quality evaluation of college English teaching based on probabilistic linguistic multiple-attribute group decision-making

IF 3.6
Ruoxi Hu , Qingmao Wang
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引用次数: 0

Abstract

The evaluation of college English teaching quality aims to comprehensively assess the achievement of teaching objectives and effectiveness through the analysis and feedback on teachers' teaching abilities, course design, and students' learning outcomes. The evaluation combines both quantitative and qualitative methods, focusing not only on the scientific and practical aspects of teaching content but also on the improvement of students' language proficiency and overall development. A scientific evaluation system encourages teachers to refine their teaching methods, enhances teaching efficiency, and provides data support for curriculum optimization, thereby continuously improving the quality of college English teaching to meet students' academic and career development needs. The quality evaluation of college English teaching is multiple-attribute group decision-making (MAGDM). To address this, combined TODIM (Logarithmic TODIM and Exponential TODIM) and PROMETHEE approaches are utilized to propose a MAGDM framework. Considering the need to capture fuzzy information during the quality evaluation process, probabilistic linguistic term sets (PLTSs) are employed. In this study, we construct the probabilistic linguistic combined TODIM-PROMETHEE (PL-Com-TODIM-PROMETHEE) approach to tackle MAGDM under PLTSs. To determine the weight values within the PLTSs framework, we employ the MEREC approach. Finally, a numerical example is presented to validate the effectiveness of the PL-Com-TODIM-PROMETHEE approach for quality evaluation of college English teaching. Through this approach, the study contributes to the advancement of quality evaluation methodologies by integrating combined TODIM and PROMETHEE within the PLTSs framework. It addresses the challenges posed by fuzzy information and provides a practical and effective approach for decision-making in the context of quality evaluation of college English teaching.
基于概率语言多属性群体决策的大学英语教学质量评价分析
大学英语教学质量评价旨在通过对教师教学能力、课程设计、学生学习成果的分析和反馈,对教学目标的实现情况和教学效果进行综合评价。评价方法定量与定性相结合,既注重教学内容的科学性和实践性,又注重学生语言能力的提高和全面发展。科学的评价体系可以鼓励教师改进教学方法,提高教学效率,为课程优化提供数据支持,从而不断提高大学英语教学质量,满足学生学业和职业发展的需要。大学英语教学质量评价是多属性群体决策(MAGDM)。为了解决这个问题,结合TODIM(对数TODIM和指数TODIM)和PROMETHEE方法提出了一个MAGDM框架。考虑到在质量评价过程中需要捕获模糊信息,采用了概率语言术语集(plts)。在本研究中,我们构建了概率语言组合TODIM-PROMETHEE (PL-Com-TODIM-PROMETHEE)方法来解决plts下的MAGDM问题。为了确定plts框架内的权重值,我们采用了merc方法。最后,通过一个算例验证了PL-Com-TODIM-PROMETHEE方法在大学英语教学质量评价中的有效性。通过这种方法,本研究通过在plts框架内整合TODIM和PROMETHEE的组合,促进了质量评估方法的进步。它解决了模糊信息带来的挑战,为大学英语教学质量评价的决策提供了一种实用有效的方法。
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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