个性化
形成性评价
个性化学习
计算机科学
路径(计算)
人机交互
生成语法
人工智能
多媒体
心理学
教学方法
合作学习
万维网
数学教育
开放式学习
程序设计语言
标识
DOI:10.1177/09637214241242459
摘要
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.
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