The ubiquity of digital devices has made it feasible to assign different tasks and levels of support to different learners, also in the classroom. Ideally, this is done with the help of formative assessment software or intelligent tutoring systems. However, personalized assignment of tasks and support levels by a teacher or teaching agent has limitations and is only one path to successful personalization. Self-regulated learning and adaptable learning activities, such as generative learning strategies and differentiating tasks, are promising paths to personalization, too, and combine well with personalized assignment. Initial examples of such combinations are presented. I argue that, in order to be maximally effective, different paths to personalized education need to be combined. This combination promises to boost both immediate learning outcomes and successful learning in the long term, and it is facilitated by recent advances in artificial intelligence.

中文翻译：

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个性化教育有多种途径，应结合起来

数字设备的普及使得在课堂上为不同的学习者分配不同的任务和支持级别成为可能。理想情况下，这是在形成性评估软件或智能辅导系统的帮助下完成的。然而，教师或教学代理对任务和支持级别的个性化分配具有局限性，并且只是成功个性化的一种途径。自我调节学习和适应性学习活动，例如生成学习策略和区分任务，也是实现个性化的有希望的途径，并且与个性化作业很好地结合起来。介绍了此类组合的初始示例。我认为，为了发挥最大的效果，个性化教育的不同途径需要结合起来。这种结合有望提高即时学习成果和长期成功学习，人工智能的最新进展也促进了这一点。