M-Powering Teachers (MPT) uses natural language processing to analyze recordings of mathematics teaching for information on student mathematical reasoning, teacher-student mathematical language, and equity-centered classroom practices. Teachers use the MPT tool to receive feedback on their teaching, and researchers can use it to replace or augment human scoring, allowing learning designs to scale more quickly and efficiently.
Heather Hill
Hazen-Nicoli Professor of Teacher Learning and Practice, Harvard Graduate School of Education
Heather Hill
Hazen-Nicoli Professor of Teacher Learning and Practice, Harvard Graduate School of Education
Heather Hill studies policies and programs designed to improve teacher and teaching quality.
Jing Liu
Assistant Professor of Education Policy, University of Maryland, College Park
Jing Liu
Assistant Professor of Education Policy, University of Maryland, College Park
Jing Liu’s research centers on student well-being and human resources policy in K-12 education, with a particular focus on the intersection of data science and education policy.
Dora Demszky
PhD candidate in Linguistics, Stanford University
Dora Demszky
PhD candidate in Linguistics, Stanford University
Dora Demszky works on developing natural language processing methods to support equitable and student-centered education.