Stimulating language learners’ engagement is essential to successful second language acquisition, but it can be hard to translate this intuition into effective learning resources. In the first large scale investigation into the linguistic and pragmatic features that make an educational conversation interesting, we collected interest ratings for 64 conversations between teachers and second language learners of English. We provide proof of concept that - despite the high degree of subjectivity involved in perceptions of interest - it is possible to extract features that make a conversation interesting for the average learner. Specifically, concreteness, comprehensibility, and uptake (i.e., the degree to which a teacher and a student’s turn build on one another) all had unique relations to interest in our data. These findings lay the foundations for future work on the optimization of AI tutors for more engaging language learning interactions.