Promoting rich discussions in mathematics classrooms: Using personalized, automated feedback to support reflection and instructional change

Jacobs, J. Scornavacco, K., Harty, C., Suresh, A., Lai, V., & Sumner, T. (2022). Promoting rich discussions in mathematics classrooms: Using personalized, automated feedback to support reflection and instructional change. Teaching and Teacher Education, 112, 103631–. https://doi.org/10.1016/j.tate.2022.103631

Oral language plays an important role in a child’s everyday life. Oral language is needed for learning to read and participating in classroom activities. Children’s oral language can be supported in the classroom through classroom talk. But ‘just getting students to talk’ can be challenging. One way to promote rich classroom talk is through the use of talk moves. Talk Moves are sentence starters that teachers and students can use to engage in conversations. For example, if a student gives a confusing response to a question, the teacher can use the ‘Say More’ move to ask the student to “Say more about that…”. This move gives the student an opportunity to clarify their thinking. However, providing professional development on talk moves could be time-consuming and expensive, requiring expert coaching and human coders.

In this study, researchers evaluated the TalkMoves application that they designed to automatically detect talk moves after teachers uploaded their classroom recording. Participants included 21 grade 4-12 teachers and their classroom. The teachers recorded a total of 233 math lessons (mean = 10; range = 3 – 21) over a four-month period. The feedback provided from the application would inform teachers on the type and frequency of talk moves used, the percentage of teacher and student talk, and a word cloud showing the most used words.

Results revealed that teachers found the application to be user-friendly but they felt the recording underestimated the amount of student talk. Teachers were more interested in feedback about teacher vs. student talk than use of talk moves, possibly due to a lack of familiar with talk moves. In fact, one teacher noted that although the feedback was useful in helping her try to change practice (e.g., use more talk moves), she was still unsure what talk moves meant and that examples and explicit teaching would have been beneficial. The most commonly used talk moves were “keeping everyone together” (e.g., asking yes/no questions, asking students to repeat) and “press for accuracy” (e.g., asking students to use mathematical vocabulary). The least used were “getting students to relate” (e.g., commenting on ideas, agreeing/disagreeing with ideas) and “press for reasoning” (e.g., asking students to explain their ideas). Teachers nominally increased their use of talk moves over time, but results were not significant. Overall, while the TalkMoves application has the potential to provide teachers with automated and individualized feedback about their classroom talk, it seems crucial that teachers have a solid understanding of talk moves. This way, when teachers are interpreting feedback from application, they can understand what they are looking at and how they could change practice. 

Blogger: Theresa Pham is a Postdoctoral Associate.