We report recent advances in intelligent tutoring systems with conversational dialogue. Macroadaptivity refers to a system's capability to select appropriate instructional tasks for the learner to work on. Microadaptivity refers to a system's capability to adapt its scaffolding while the learner is working on a particular task. Learning progressions and deeper dialogue and natural language processing techniques are key features of DeepTutor, the first intelligent tutoring system based on learning progressions.

The past five years have seen dramatic advances in planning algorithms, with an emphasis on propositional methods such as GRAPHPLAN and compilers that convert planning problems into propositional conjunctive normal form formulas for solution using systematic or stochastic SAT methods. In this survey, I explain the latest techniques and suggest areas for future research.