In search for the most informative data for feedback generation: Learning analytics in a data-rich context
作者：
Highlights：
• Formative assessment data have high predictive power in generating learning feedback.
• Track data from e-tutorial systems are second-best predictors for timely feedback.
• Predictive power of LMS data falls short in LA applications with rich data sources.
• Learning dispositions take a unique position being complementary to all other data.
• Combination of several data sources in LA is key to get timely, predictive feedback.
摘要
•Formative assessment data have high predictive power in generating learning feedback.•Track data from e-tutorial systems are second-best predictors for timely feedback.•Predictive power of LMS data falls short in LA applications with rich data sources.•Learning dispositions take a unique position being complementary to all other data.•Combination of several data sources in LA is key to get timely, predictive feedback.
论文关键词：Blended learning,Dispositional learning analytics,e-Tutorials,Formative assessment,Learning dispositions
论文评审过程：Available online 28 June 2014.
论文官网地址：https://doi.org/10.1016/j.chb.2014.05.038
