Data literacy for learning analytics

A. Wolff, John Moore, Z. Zdráhal, Martin Hlosta, Jakub Kuzilek
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引用次数: 12

Abstract

This workshop explores how data literacy impacts on learning analytics both for practitioners and for end users. The term data literacy is used to broadly describe the set of abilities around the use of data as part of everyday thinking and reasoning for solving real-world problems. It is a skill required both by learning analytics practitioners to derive actionable insights from data and by the intended end users, such that it affects their ability to accurately interpret and critique presented analysis of data. The latter is particularly important, since learning analytics outcomes can be targeted at a wide range of end users, some of whom will be young students and many of whom are not data specialists. Whilst data literacy is rarely an end goal of learning analytics projects, this workshop aims to find where issues related to data literacy have impacted on project outcomes and where important insights have been gained. This workshop will further encourage the sharing of knowledge and experience through practical activities with datasets and visualisations. This workshop aims to highlight the need for a greater understanding of data literacy as a field of study, especially with regard to communicating around large, complex, data sets.
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学习分析的数据素养
本次研讨会探讨了数据素养对从业者和最终用户学习分析的影响。“数据素养”一词被广泛地用于描述将数据作为日常思考和推理的一部分来解决现实世界问题的一系列能力。这是学习分析从业者从数据中获得可操作见解的技能,也是预期的最终用户所需要的技能,因为它会影响他们准确解释和批评呈现的数据分析的能力。后者尤其重要,因为学习分析的结果可以针对广泛的最终用户,其中一些是年轻的学生,其中许多人不是数据专家。虽然数据素养很少是学习分析项目的最终目标,但本次研讨会旨在找出与数据素养相关的问题对项目成果的影响,以及从中获得的重要见解。本次研讨会将通过数据集和可视化的实践活动进一步鼓励知识和经验的分享。本次研讨会旨在强调需要更好地理解数据素养作为一个研究领域,特别是在围绕大型、复杂的数据集进行交流方面。
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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