This article describes research results based on multiple years of experimentation and real-world experience with an adaptive tutoring system named Wayang Outpost. The system represents a novel adaptive learning technology that has shown successful outcomes with thousands of students, and provided teachers with valuable information about students' mathematics performance. We define progress in three areas: improved student "cognition," "engagement," and "affect," and we attribute this improvement to specific components and interventions that are inherently "affective," "cognitive," and "metacognitive" in nature. For instance, improved student "cognitive outcomes" have been measured with pre-post tests and state standardized tests, and achieved due to personalization of content and math fluency training. Improved student "engagement" was achieved by supporting students' metacognition and motivation via affective learning companions and progress reports, measured via records of student gaming of the system. Student "affect" within the tutor was measured through sensors and student self-reports, and supported through affective learning companions and progress reports. Collectively, these studies elucidate a suite of effective strategies to support advanced personalized learning via an intelligent adaptive tutor that can be tailored to the individual needs, emotions, cognitive states, and metacognitive skills of learners.