Dorottya Demszky
Automated Feedback Improves Teachers’ Questioning Quality in Brick-and-Mortar Classrooms: Opportunities for Further Enhancement
Topics: Teacher and Leader DevelopmentAI-powered professional learning tools that provide teachers with individualized feedback on their instruction have proven effective at improving instruction and student engagement in virtual learning contexts. Despite the need for consistent, personalized professional learning in K-12 settings… more →
Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise
Topics: Student LearningGenerative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive,… more →
Computational Language Analysis Reveals that Process-Oriented Thinking About Belonging Aids the College Transition
Dorottya Demszky, C. Lee Williams, Shannon T. Brady, Shashanka Subrahmanya, Eric Gaudiello, Gregory M. Walton, Johannes C. Eichstaedt.Tags: College readinessInequality in college has both structural and psychological causes; these include the presence of self-defeating beliefs about the potential for growth and belonging. Such beliefs can be addressed through large-scale interventions in the college transition (Walton & Cohen, 2011; Walton et al… more →
A Quantitative Study of Mathematical Language in Upper Elementary Classrooms
Topics: MethodsThis study provides the first large-scale quantitative exploration of mathematical language use in upper elementary U.S. classrooms. Our approach employs natural language processing techniques to describe variation in teachers’ and students’ use of mathematical language in 1,657 fourth and fifth… more →
Scaffolding Middle-School Mathematics Curricula With Large Language Models
Topics: MethodsTags: Mathematics educationDespite well-designed curriculum materials, teachers often face challenges in their implementation due to diverse classroom needs. This paper investigates whether Large Language Models (LLMs) can support middle-school math teachers by helping create high-quality curriculum scaffolds, which we… more →
Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform
Topics: Student LearningProviding ample opportunities for students to express their thinking is pivotal to their learning of mathematical concepts. We introduce the Talk Meter, which provides in-the-moment automated feedback on student-teacher talk ratios. We conduct a randomized controlled trial on a virtual math… more →
Sit Down Now: How Teachers' Language Reveals the Dynamics of Classroom Management Practices
Teachers’ attitudes and classroom management practices critically affect students’ academic and behavioral outcomes, contributing to the persistent issue of racial disparities in school discipline. Yet, identifying and improving classroom management at scale is challenging, as existing methods… more →
Can Automated Feedback Improve Teachers’ Uptake of Student Ideas? Evidence From a Randomized Controlled Trial In a Large-Scale Online Course
Topics: Teacher and Leader DevelopmentProviding consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their… more →
M-Powering Teachers: Natural Language Processing Powered Feedback Improves 1:1 Instruction and Student Outcomes
Topics: Teacher and Leader DevelopmentAlthough learners are being connected 1:1 with instructors at an increasing scale, most of these instructors do not receive effective, consistent feedback to help them improved. We deployed M-Powering Teachers, an automated tool based on natural language processing to give instructors feedback… more →
The NCTE Transcripts: A Dataset of Elementary Math Classroom Transcripts
Topics: MethodsClassroom discourse is a core medium of instruction --- analyzing it can provide a window into teaching and learning as well as driving the development of new tools for improving instruction. We introduce the largest dataset of mathematics classroom transcripts available to researchers, and… more →
Computationally Identifying Funneling and Focusing Questions in Classroom Discourse
Topics: Student LearningResponsive teaching is a highly effective strategy that promotes student learning. In math classrooms, teachers might funnel students towards a normative answer or focus students to reflect on their own thinking, deepening their understanding of math concepts. When teachers focus, they treat… more →
Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions
Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather C. Hill, Dan Jurafsky, Tatsunori Hashimoto.Topics: MethodsTags: Instructional practicesIn conversation, uptake happens when a speaker builds on the contribution of their interlocutor by, for example, acknowledging, repeating or reformulating what they have said. In education, teachers' uptake of student contributions has been linked to higher student achievement. Yet measuring and… more →