回顾英国开放大学学习分析干预的三个案例研究

B. Rienties, Avinash Boroowa, Simon Cross, Lee Farrington-Flint, C. Herodotou, L. Prescott, Kevin Mayles, Tom Olney, Lisette Toetenel, J. Woodthorpe
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引用次数: 18

摘要

本研究提供了一个概念性框架,组织如何大规模采用基于证据的干预措施,以及机构如何评估此类干预措施的成本和收益。以英国开放大学(Open University UK)开发的新概念模型为基础,我们将分析三个基于证据的干预案例研究。通过在开放大学的五个院系和学科中与90多个大型模块进行为期两年的合作,Analytics4Action为在各自背景下与关键利益相关者一起工作提供了一种自下而上的方法。利用Yin[1]的嵌入式案例研究方法的原理,通过比较11079名学习者的学习行为、满意度和表现,研究结果表明,三种学习设计中的每一种都导致了满意的学生,学生保留率平均到良好。在第二部分中,我们强调了三个模块团队基于实时分析进行了演示干预,即初始用户数据表明VLE行为符合预期。在2-5年内,我们希望能够提供丰富、有力的证据基础,以展示学习分析如何帮助教师做出明智、及时和成功的干预措施,从而帮助学习者取得学习成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reviewing three case-studies of learning analytics interventions at the open university UK
This study provides a conceptual framework how organizations may adopt evidence-based interventions at scale, and how institutions may evaluate the costs and benefits of such interventions. Building on a new conceptual model developed by the Open University UK (OU), we will analyse three case-studies of evidence-based interventions. By working with 90+ large-scale modules for a period of two years across the five faculties and disciplines within the OU, Analytics4Action provides a bottom-up-approach for working together with key stakeholders within their respective contexts. Using principles of embedded case-study approaches by Yin [1], by comparing the learning behavior, satisfaction and performance of 11079 learners the findings indicated that each of the three learning designs led to satisfied students and average to good student retention. In the second part we highlighted that the three module teams made in-presentation interventions based upon real-time analytics, whereby initial user data indicated VLE behaviour in line with expectations. In 2-5 years, we hope that a rich, robust evidence-base will be presented to show how learning analytics can help teachers to make informed, timely and successful interventions that will help learners to achieve their learning outcomes.
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