Engaging messages delivered by teachers are a key aspect of the classroom discourse that influences student outcomes. However, improving this communication is challenging due to difficulties in obtaining observations. This study presents a methodology for efficiently extracting actual observations of engaging messages from audio-recorded lessons. We collected 2,477 audio-recorded lessons from 75 teachers over two academic years. Using automatic transcription and keyword-based filtering analysis, we identified and classified engaging messages. This method reduced the information to be analysed by 90%, optimising the time and resources required compared to traditional manual coding. Subsequent descriptive analysis revealed that the most used messages emphasised the future benefits of participating in school activities. In addition, the use of engaging messages decreased as the academic year progressed. This study offers insights for researchers seeking to extract information from teachers' discourse in naturalistic settings and provides useful information for designing interventions to improve teachers' communication strategies. Keywords: Teacher education; Technology; Discourse; Secondary education; Engagement 1. Introduction Teachers' discourse has the power to shape students' outcomes (Caldarella et al., 2023; Howe & Abedin, 2013; Mercer, 2010).

I received my copy today and instantly decided I would be using it in several of the courses I teach for pre-service teachers. They have been asking for a book like this for years, but the existing books were aimed at the wrong audience, had content that was oversimplified (or overly complex), or failed to incorporate important current research. Dr. Fredricks' book masterfully incorporates the most relevant research with perfect tone and an engaging narrative. There's no way I'll be assigning a 100 textbook when this new book does so much more at less than a third the price.

Good readers ask questions during reading, and this is presumed to improve their text comprehension. But what about not-so-good readers? Does question asking promote comprehension for struggling readers and, if so, how can we best support these students? This paper examines question generation among low-performing sixth-graders who read moderately-challenging science texts. It characterizes the nature of students’ questions and describes the effects of a video-based peer modeling intervention on their question asking and reading comprehension. In contrast to previous research, this study found that students asked a large number of deep reasoning questions, particularly those related to identifying goals, processes, causes, and consequences. However, such questions were not generally associated with greater understanding. Only two types of deep reasoning questions were related to text comprehension—those that were not answered in the text (directly or indirectly) and those that students labeled as “I’m Confused” questions. The study also found that readers who were exposed to video-based peer modeling of question generation asked more of these types of questions and scored significantly higher on multiple measures of text comprehension. These findings have implications for the design of systems to support struggling readers and for theory-building about question generation.