iSTART is an intelligent tutoring system designed to provide self-explanation instruction and practice to improve students' comprehension of complex, challenging text. This study examined the effects of extended game-based practice within the system as well as the effects of two metacognitive supports implemented within this practice. High school stu-dents (n = 234) were either assigned to an iSTART treatment condition or a control condition. Within the iSTART condition, students were assigned to a 2x2 design in which students provided "self-assessments" of their performance or were transferred to Coached Practice if their performance did not reach a certain "performance threshold." Those receiving iSTART training produced higher self-explanation and inference-based comprehension scores. However, there were no direct effects of either metacognitive support on these learning outcomes. [This paper was published in: R. Baker & E. Andre (Eds.), "Proceedings of the 18th International Conference on Artificial Intelligence in Education" (pp. 201-211), Wuhan, China: Springer.]