成功秘诀:在连接学习分析工具包中使用xAPI的经验教训

Aneesha Bakharia, Kirsty Kitto, A. Pardo, D. Gašević, S. Dawson
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引用次数: 48

摘要

学习分析研究面临的一个持续挑战是从多种技术中可扩展地派生用户交互数据。随着教育工作者接受越来越多的社交和内容相关技术,与这一挑战相关的复杂性也在增加。体验API (xAPI)以及用户特定记录存储的开发被吹捧为解决这一挑战的一种手段,但是在学习分析中使用xAPI时必须考虑许多微妙的问题。本文概述了在通用系统分析解决方案(称为连接学习分析(CLA)工具包)中使用xAPI的复杂性和挑战。强调了设计的重要性,以及公共词汇表和xAPI Recipes的概念。关于词汇表和语句之间的结构关系的早期决策可以促进或阻碍后来的分析解决方案。CLA工具箱案例研究为我们提供了一种检查当前xAPI规范的优点和缺点的方法,最后我们提出了如何通过使用JSON-LD以机器可读的形式形式化Recipes来改进xAPI的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recipe for success: lessons learnt from using xAPI within the connected learning analytics toolkit
An ongoing challenge for Learning Analytics research has been the scalable derivation of user interaction data from multiple technologies. The complexities associated with this challenge are increasing as educators embrace an ever growing number of social and content-related technologies. The Experience API (xAPI) alongside the development of user specific record stores has been touted as a means to address this challenge, but a number of subtle considerations must be made when using xAPI in Learning Analytics. This paper provides a general overview to the complexities and challenges of using xAPI in a general systemic analytics solution - called the Connected Learning Analytics (CLA) toolkit. The importance of design is emphasised, as is the notion of common vocabularies and xAPI Recipes. Early decisions about vocabularies and structural relationships between statements can serve to either facilitate or handicap later analytics solutions. The CLA toolkit case study provides us with a way of examining both the strengths and the weaknesses of the current xAPI specification, and we conclude with a proposal for how xAPI might be improved by using JSON-LD to formalise Recipes in a machine readable form.
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