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Dorottya Demszky
Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise
Topics: Student LearningTags: Generative artificial intelligence (AI) in education, Instructional design, Instructional practices, Student engagement, Student supportsGenerative AI, particularly Large Language Models (LLMs), can expand access to expert guidance in domains like education, where such support is often limited. We introduce Tutor CoPilot, a Human-AI system that models expert thinking to assist tutors in real time. In a randomized controlled trial… more →
Do As I Say: What Teachers’ Language Reveals About Classroom Management Practices
Topics: Student Well-BeingClassroom management critically affects students’ academic and behavioral outcomes, yet we lack quantitative methods for observing these practices at scale. This study develops and validates language-based measures of classroom management—such as responding to student behavior and issuing verbal… more →
Facilitating Evidence-Based Instructional Coaching With Automated Feedback on Teacher Discourse
Topics: Teacher and Leader DevelopmentInstructional coaching often aims to ground teacher professional learning in classroom evidence, yet it is labor-intensive for coaches to obtain and curate such evidence. This study explores possibilities for utilizing an automated feedback tool to support evidence-based reasoning in coaching.… more →
From Sentence-Corrections to Deeper Dialogue: Qualitative Insights from LLM and Teacher Feedback on Student Writing
Topics: MethodsEffective writing feedback is a powerful tool for enhancing student learning, encouraging revision, and increasing motivation and agency. Yet, teachers face many challenges that prevent them from consistently providing effective writing feedback. Recent advances in generative artificial… more →
Scaffolding Middle-School Mathematics Curricula With Large Language Models
Topics: MethodsTags: Mathematics educationDespite well-designed curriculum materials, teachers often face challenges implementing them due to diverse classroom needs. This paper investigates whether large language models (LLMs) can support middle school math teachers by helping create highquality curriculum scaffolds, which we define as… more →
Does Increased Agency Improve the Effectiveness of Self-Directed Professional Learning for Educators?
Dorottya Demszky, Heather C. Hill, Eric S. Taylor, Ashlee Kupor, Deepak Varuvel Dennison, Chris Piech.Topics: Teacher and Leader DevelopmentThe role of teacher agency in professional learning has been the subject of several qualitative studies but has not yet been tested in an experimental setting. To provide causal evidence of the impact of teacher agency on the effectiveness of professional learning, we conducted a preregistered… more →
Educator Attention: How computational tools can systematically identify the distribution of a key resource for students
Topics: MethodsEducator attention is critical for student success, yet how educators distribute their attention across students remains poorly understood due to data and methodological constraints. This study presents the first large-scale computational analysis of educator attention patterns, leveraging over… more →
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 →
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 →
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 →
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 →