Data analysis to guide the design and deployment of learning experiences has been in use in educational institutions for decades. While this has made it possible to predict retention, flags students at risk and more clearly assesses performance across a range of indicators, few benefits visible to students have resulted. Recent attempts to design learner-facing analytics seem to also have met with indifferent results as they appear to have neglected to focus on student personality and motivation or to train students appropriately to decipher LA-based feedback.

The aim of this study is to investigate why current Learning Analytics (LA) systems have so little impact on student motivation. A further goal has been to scrutinize the latest research for potential grounding in theoretical concepts generally – but with emphasis on motivation.

Results show that, with few exceptions, neither instructor- nor learner-facing LA currently in use at universities take into consideration student personalities as neither are grounded in appropriate theory. This study contributes to the field of LA and Motivation by providing a clear (if bleak) picture of the lack of focus on student personality and motivation in terms of LA feedback. It is, therefore, timely that to remind the research community that an understanding of the learner’s personality, attributes, and sources of motivation is central to the effectiveness of any feedback design. We see this paper as a starting point for a much-needed deeper discussion.

数十年来，教育机构一直在使用数据分析来指导学习体验的设计和部署。虽然这使得预测保留率成为可能，标记有风险的学生并更清楚地评估一系列指标的表现，但对学生来说几乎没有什么好处。最近设计面向学习者的分析的尝试似乎也遇到了冷漠的结果，因为他们似乎忽略了关注学生的个性和动机或适当地训练学生解读基于洛杉矶的反馈。

本研究的目的是调查为什么当前的学习分析 (LA) 系统对学生动机的影响如此之小。另一个目标是仔细审查最新的研究，以了解一般理论概念的潜在基础——但重点是动机。

结果表明，除了少数例外，目前在大学使用的面向教师和面向学习者的 LA 都没有考虑到学生的个性，因为两者都没有以适当的理论为基础。本研究通过清晰地（如果黯淡）描绘了在洛杉矶反馈方面缺乏对学生个性和动机的关注，从而为洛杉矶和动机领域做出了贡献。因此，及时提醒研究界，了解学习者的个性、属性和动机来源是任何反馈设计有效性的核心。我们将本文视为进行急需的更深入讨论的起点。