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Personal Online Analytic Learning System (POALS) is a web-based learning management system (LMS) developed to help learners succeed when taking online learning courses. The system was developed using the open edX LMS and has been tested with learners in 3 online classes at Tokyo Tech. 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 new component was added called AI Kaku which is AI assisted writing tool. 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. Regarding research achievements, one peer review journal paper was published, one invited conference talk, and 9 conference papers were presented at domestic and international conferences. In addition, a doctoral student conducting this research won the best presentation award at the IEEE Teaching, Assessment and Learning for Engineering (TALE) conference in Dec. 2021 based upon this research.