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The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement

机译:RISE框架:使用学习分析功能自动识别开放式教育资源以进行持续改进

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The RISE (Resource Inspection, Selection, and Enhancement) Framework is a framework supporting the continuous improvement of open educational resources (OER). ?The framework is an automated process that identifies learning resources that should be evaluated and either eliminated or improved. ?This is particularly useful in OER contexts where the copyright permissions of resources allow for remixing, editing, and improving content.? The RISE Framework presents a scatterplot with resource usage on the x-axis and grade on the assessments associated with that resource on the y-axis.? This scatterplot is broken down into four different quadrants (the mean of each variable being the origin) to find resources that are candidates for improvement.? Resources that reside deep within their respective quadrant (farthest from the origin) should be further analyzed for continuous course improvement.? We present a case study applying our framework with an Introduction to Business course. Aggregate resource use data was collected from Google Analytics and aggregate assessment data was collected from an online assessment system.? Using the RISE Framework, we successfully identified resources, time periods, and modules in the course that should be further evaluated for improvement.
机译:RISE(资源检查,选择和增强)框架是支持开放式教育资源(OER)持续改进的框架。该框架是一个自动化的过程,该过程确定应评估,消除或改善的学习资源。这在OER上下文中特别有用,在OER上下文中,资源的版权许可允许重新混合,编辑和改进内容。 RISE框架在x轴上显示了资源使用情况的散点图,在y轴上显示了与该资源相关的评估的等级。此散点图分为四个不同的象限(每个变量的均值是原点),以查找可以改进的资源。应该进一步分析位于其各自象限(离原点最远)内的资源,以便不断改进过程。我们通过“商业概论”课程介绍了应用我们的框架进行的案例研究。从Google Analytics(分析)收集了资源使用总量数据,并从在线评估系统收集了资源评估数据。使用RISE框架,我们成功地确定了课程中应进一步评估改进的资源,时间段和模块。

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