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Improving the quality of teaching by utilising written student feedback: A streamlined process

机译:利用书面学生反馈提高教学质量:简化的过程

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Currently student feedback is mainly evaluated with quantitative methods since qualitative analysis has been highly effort intensive. In this article, we present a process for tapping into the resource of responses to open-ended feedback questions by using a topic-modelling approach that goes beyond listing modelling outcomes. The objective of this study is to present a streamlined, yet rigorous, process for analysing large amounts of written feedback that connects qualitative findings to existing literature, theories and quantitative feedback. The topic models are created using the Latent Dirichlet Allocation (LDA) method, after which qualitative and quantitative evaluation methods are used to validate the topic outcomes. The proposed process can help educators analyse teaching quality on programmeor institution-wide level, or on single courses with a very large number of students. The process systematizes and combines existing processes, is repeatable, and can serve as a basis for richer analysis for educators. In student evaluation of teaching (SET) research, it advances the state of the art in applied topic modelling by demonstrating how to validate the topics via thematic analysis and by connecting them to theoretical frameworks and quantitative data. Previous topic modelling studies in this field follow mainly descriptive approaches. We demonstrate the process with feedback data collected from 6087 student evaluations of university courses and confirm that quantitative feedback variables can be used to validate qualitative feedback topic-modelling outcomes and thematic analysis provides a more in-depth explanation of the topics. We additionally find that the proposed topic modelling approach discovers new constructs of SET that cannot be distinguished from quantitative SET measures. The main limitation of the study is that the proposed process is novel and requires further evaluation to establish its full validity.
机译:目前,学生反馈主要通过定量方法评估,因为定性分析一直是强烈的密集。在本文中,我们通过使用超出列表建模结​​果的主题建模方法,提出了一种进入对开放式反馈问题的响应资源的过程。本研究的目的是提供一种简化但严谨的流程,用于分析大量书面反馈,这些反馈将定性结果与现有文献,理论和定量反馈联系起来。主题模型是使用潜在的dirichlet分配(LDA)方法创建的,之后使用定性和定量评估方法来验证主题结果。拟议的进程可以帮助教育工作者分析方案机构范围内的教学质量,或在具有很多学生的单一课程上。该过程系统化并结合了现有的过程,是可重复的,可以作为教育工作者更丰富的分析的基础。在学生教学评估(集)研究中,它通过演示如何通过主题分析和将其连接到理论框架和定量数据来实现应用主题建模中的最新技术。前提主题在此领域的建模研究主要遵循描述性方法。我们展示了从大学课程的6087名学生评估中收集的反馈数据的过程,并确认定量反馈变量可用于验证定性反馈主题建模结果,主题分析提供了更深入的话题解释。我们还发现,所提出的主题建模方法发现了无法与定量设定措施不同的集合构造。研究的主要限制是,拟议的过程是新颖的,需要进一步评估,以确定其全部有效性。

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