学习分析向前发展:专家观点

Rebecca Ferguson, D. Clow, D. Griffiths, Andrew Brasher
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引用次数: 19

摘要

学习分析包括测量、收集、分析和报告关于学习者及其环境的数据,以理解和优化学习及其发生的环境。自2011年作为一个独立的领域出现以来,学习分析发展迅速,世界各地的早期采用者已经在开发和部署这些新工具。本文报告了一项研究,该研究调查了到2025年该领域可能如何发展,以便为那些关注学习分析实施的人提供行动建议。这项研究采用了政策德尔菲方法,向该领域的国际专家提出了一系列未来的设想,并要求对这些设想的可取性和可行性以及所需采取的行动作出反应。收到了来自21个国家的103人的回复。对问卷进行主题编码,采用Cohen’s kappa系数对问卷的信度进行检验,若kappa低于0.6,则对问卷进行重新编码。在数据中确定的七个主要主题是权力,教学法,有效性,监管,复杂性,伦理和影响。本文详细考虑了这些主题及其对学习分析实施的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Moving Forward with Learning Analytics: Expert Views
Learning analytics involve the measurement, collection, analysis, and reporting of data about learners and their contexts, in order to understand and optimise learning and the environments in which it occurs. Since emerging as a distinct field in 2011, learning analytics has grown rapidly, and early adopters around the world are already developing and deploying these new tools. This paper reports on a study that investigated how the field is likely to develop by 2025, in order to make recommendations for action to those concerned with the implementation of learning analytics. The study used a Policy Delphi approach, presenting a range of future scenarios to international experts in the field and asking for responses related to the desirability and feasibility of these scenarios, as well as actions that would be required. Responses were received from 103 people from 21 countries. Responses were coded thematically, inter-rater reliability was checked using Cohen’s kappa coefficient, and data were recoded if kappa was below 0.6. The seven major themes that were identified within the data were power, pedagogy, validity, regulation, complexity, ethics, and affect. The paper considers in detail each of these themes and its implications for the implementation of learning analytics.
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