Personalized Online Adaptive Learning System

个性化在线自适应学习系统（POALS）是一个基于网络的学习管理系统（LMS）的附加组件，旨在帮助学习者在学习在线学习课程时取得成功。它由三个部分组成：1）元认知导师，为学生提供对在线学习至关重要的自主学习所需的元认知技能，2）自适应引擎，帮助学生管理元认知辅导与领域知识学习的认知压力，（3）分析仪表板基于学生对元认知导师的反馈，向教师反馈可能需要学习者干预的地方。2021年，POALS的元认知导师的变体被添加到AI Kaku中，AI Kaku是PI实验室创建的AI辅助写作工具。2022年的重点是通过游戏化和虚拟现实方面的能力建设进行适应性学习。这项研究的主要内容包括哪些元认知技能可以独立学习，哪些需要教师的推动，哪些算法在考虑元认知措施时最适合知识追踪，以及学习者元认知反思的文本数据如何用于学习分析。2022年的研究成果包括发表1篇同行评审期刊论文和9次国内和国际会议报告。

The Personalized Online Adaptive Learning System (POALS) is a web-based add-on to a learning management system (LMS) developed to help learners succeed when taking online learning courses. It is made up of three components: 1) the Metacognitive Tutor to equip students with metacognitive skills needed for autonomous learning crucial to online learning, 2) the Adaptive Engine to help students manage the cognitive strain of having metacognitive tutoring alongside domain knowledge learning, and the 3) Analytics Dashboard based on student responses on the Metacognitive Tutor to give feedback to teachers on where learner interventions might be needed. In 2021, a variation of POALS' Metacognitive Tutor was added to AI Kaku, an AI-assisted writing tool also created at the PI's laboratory. In 2022, the focus had been on adaptive learning through capacity-building in gamification and virtual reality. Key takeaways from this research include which metacognitive skills can be learned independently and which ones require nudging from teachers, which algorithms can work best for knowledge tracing while considering metacognitive measures, and how text data from learner metacognitive reflections can be used for learning analytics. Research achievements for 2022 include one peer review journal paper published and 9 conference presentations for both domestic and international conferences.