Personalized education—the systematic adaptation of instruction to individual learners—has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when relevant learner characteristics are measured repeatedly during the learning process and when these data are used to adapt instruction in a systematic way. Building on these observations, we propose a novel, dynamic framework of personalization that conceptualizes learners as dynamic entities that change during and in interaction with the instructional process. As these dynamics manifest on different timescales, so do the opportunities for instructional adaptations—ranging from setting appropriate learning goals at the macroscale to reacting to affective-motivational fluctuations at the microscale. We argue that instructional design needs to take these dynamics into account in order to adapt to a specific learner at a specific point in time. Finally, we provide some examples of successful, dynamic adaptations and discuss future directions that arise from a dynamic conceptualization of personalization.

个性化教育-系统地适应个体学习者的教学-是一个长期的目标。我们回顾了在实验室，教室和数字学习环境中进行的个性化教育研究。在所有学习环境中，我们发现，在学习过程中反复测量相关学习者的特征，以及将这些数据用于系统地适应教学时，个性化才最成功。基于这些观察，我们提出了一种新颖的，动态的个性化框架，该框架将学习者概念化为在教学过程中以及与之互动的过程中发生变化的动态实体。由于这些动态体现在不同的时间尺度上，教学适应的机会也是如此—从在宏观上设定适当的学习目标到对微观上的情感动机波动做出反应。我们认为教学设计需要考虑这些动态因素，以便在特定的时间点适应特定的学习者。最后，我们提供了一些成功的动态调整示例，并讨论了动态个性化概念化所产生的未来方向。