Abstract
Whole class discussions (WCDs) are an important pedagogical tool for mathematics classes but are challenging to characterize across large numbers of observations because of their dynamic and complex nature. In this paper, we report on an exploratory method to characterize WCDs in mathematics classes across large numbers of observations that we refer to as Conversation Profile Analysis (CPA). CPA uses Latent Class Modeling (LCM) with live observation data to generate profiles of WCDs in middle-grade mathematics classes. We report on our exploratory use of CPA to analyze observation data from 259 WCDs about data and statistics in middle school classes making use of an innovative approach to instruction called Data Modeling. We identified 4 profiles of WCDs and found that these profiles varied in likelihood across time and were associated with different ways students talked about key mathematical ideas. We also discuss broader implications of the CPA approach to studying WCDs in math classes.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
