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  1. Hilary Kreisberg
  2. http://www.lesley.edu/center/math-achievement
  3. Director, Center for Mathematics Achievement
  4. Presenter’s NSFRESOURCECENTERS
  5. Lesley University
  1. Anthony Botelho
  2. Research Scientist
  3. Presenter’s NSFRESOURCECENTERS
  4. Worcester Polytechnic Institute
  1. Cristina Heffernan
  2. Math Education Specialist, ASSISTments
  3. Presenter’s NSFRESOURCECENTERS
  4. Worcester Polytechnic Institute
  1. Neil Heffernan
  2. http://www.neilheffernan.net/
  3. Professor
  4. Presenter’s NSFRESOURCECENTERS
  5. Worcester Polytechnic Institute
Facilitators’
Choice

Putting Teachers in the Driver’s Seat: Using Machine Learning to Personalize ...

NSF Awards: 1822830

2019 (see original presentation & discussion)

Grades 6-8

Tools for communication are getting smarter; when someone replies to a text message or email, predictive or ‘suggested messages’ automatically pop-up as quick options. Users can easily select a suggestion rather than spending time writing their own message, thus allowing technology to facilitate human-to-human interactions. Such means of enhanced communication to facilitate dialogue does not yet exist in most educational contexts. Our project, DRIVER-SEAT, applies computer science technology to mathematics education to support teachers in providing feedback more efficiently. Middle school mathematics teachers are faced daily with hundreds of student responses to open-ended questions. Educators know that feedback is an important part of the learning process, but teachers generally do not have enough time to read through all the student responses and give the much needed constructive feedback. That’s why we’re using machine learning and natural language processing to help personalize and streamline data-driven teacher-student dialogues. Hence, our project: Dialogue Reinforcement Infrastructure for Volitional Exploratory Research - Soliciting Effective Actions from Teachers (DRIVER-SEAT).

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