AuthorIT and TutorIT represent a fundamentally different approach to building and delivering adaptive learning systems. Intelligent Tutoring Systems (ITS) guide students as they solve problems. BIG DATA systems make pedagogical decisions based on average student performance. Decision making in AuthorIT and TutorIT is designed to model the human tutoring process as a whole. Just as good human tutors need to know the subject matter, AuthorIT is used to systematically identify what students need to learn for success. TutorIT takes this information as input and makes all pedagogical decisions automatically. This dramatically reduces the time and expense of building adaptive learning systems, while simultaneously having the potential of ensuring predetermined levels of mastery.