Rose E. Wang
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… 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 →
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 →