Many intelligent tutoring systems (ITSs) offer feedback and guidance through structured dialogs with their students, which often take the form of a sequence of hints. However, it is often difficult to replicate the complexity and responsiveness of human conversation with current natural language understanding and production technologies. Although ITSs reveal enough information to continue solving a problem, the conversations are not very engaging. To enhance engagement, the current study manipulated tutorial dialog by transforming them into a trialog by adding another student. Our intention was to advance the help offered by the system by putting students in a position to help each other, as well as make sense of the help offered by the ITS. The present paper attempts to show that conversations, either with the system or with a peer, are important design considerations when building an effective ITS.