  Transcripts of teaching episodes can be effective tools to understand
discourse patterns in classroom instruction. According to most educational
experts, sustained classroom discourse is a critical component of equitable,
engaging, and rich learning environments for students. This paper describes the
TalkMoves dataset, composed of 567 human-annotated K-12 mathematics lesson
transcripts (including entire lessons or portions of lessons) derived from
video recordings. The set of transcripts primarily includes in-person lessons
with whole-class discussions and/or small group work, as well as some online
lessons. All of the transcripts are human-transcribed, segmented by the speaker
(teacher or student), and annotated at the sentence level for ten discursive
moves based on accountable talk theory. In addition, the transcripts include
utterance-level information in the form of dialogue act labels based on the
Switchboard Dialog Act Corpus. The dataset can be used by educators,
policymakers, and researchers to understand the nature of teacher and student
discourse in K-12 math classrooms. Portions of this dataset have been used to
develop the TalkMoves application, which provides teachers with automated,
immediate, and actionable feedback about their mathematics instruction.
