Contextualising Learning Analytics with Classroom Observations: A Case study

IxD&A Pub Date : 2020-05-10 DOI:10.55612/s-5002-044-004
M. Eradze, M. Rodríguez-Triana, Nikola Milikić, M. Laanpere, Kairit Tammets
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Abstract

Educational processes take place in physical and digital places. To analyse educational processes, Learning Analytics (LA) enable data collection from the digital learning context. At the same time, to gain more insights, the LA data can be complemented with the data coming from physical spaces enabling Multimodal Learning Analytics (MMLA). To interpret this data, theoretical grounding or contextual information is needed. Learning designs (LDs) can be used for contextualisation, however, in authentic scenarios the availability of machine-readable LD is scarce. We argue that Classroom Observations (COs), traditionally used to understand educational processes taking place in physical space, can provide the missing context and complement the data from the co-located classrooms. This paper reports on a co-design case study from an authentic scenario that used CO to make sense of the digital traces. In this paper we posit that the development of MMLA approaches can benefit from co-design methodologies; through the involvement of the end-users (project managers) in the loop, we illustrate how these data sources can be systematically integrated and analysed to better understand the use of digital resources. Results indicate that CO can drive sense-making of LA data where predefined LD is not available. Furthermore, CO can support layered contextualisation depending on research design, rigour and systematic documentation/data collection efforts.Also, co-designing the MMLA solution with the end-users proved to be a useful approach.
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情境化学习分析与课堂观察:个案研究
教育过程在物理和数字环境中进行。为了分析教育过程,学习分析(LA)可以从数字学习环境中收集数据。与此同时,为了获得更多的见解,可以将LA数据与来自物理空间的数据进行补充,从而实现多模式学习分析(MMLA)。为了解释这些数据,需要理论基础或上下文信息。学习设计(LD)可用于情境化,然而,在真实场景中,机器可读LD的可用性是稀缺的。我们认为,传统上用于理解发生在物理空间中的教育过程的课堂观察(COs)可以提供缺失的背景,并补充来自同一地点教室的数据。本文报告了一个来自真实场景的协同设计案例研究,该场景使用CO来理解数字痕迹。在本文中,我们假设MMLA方法的发展可以受益于协同设计方法;通过最终用户(项目经理)在循环中的参与,我们说明了如何系统地集成和分析这些数据源,以更好地理解数字资源的使用。结果表明,在预定义的LD不可用的情况下,CO可以驱动LA数据的意义生成。此外,CO可以支持分层情境化,这取决于研究设计、严谨性和系统的文档/数据收集工作。此外,与最终用户共同设计MMLA解决方案被证明是一种有用的方法。
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