9/1/16-8/31/20 PIs: Beverly Woolf, Thomas Murray, University of Massachusetts Amherst (Award Details) Ivon Arroyo, Worcester Polytechnic Institute (Award Details) Margrit Betke, Stan Sclaroff, Boston University (Award Details) John Magee, Rutgers University New Brunswick (Award Details) This INT project integrates prior work from two well-developed NSF-sponsored projects on (i) advanced computer vision and (ii) affect detection […]
Tag Archives: Intelligent tutors and tools
EXP: Data-Driven Support for Novice Programmers
9/1/16-8/31/19 PIs: Tiffany Barnes, Min Chi North Carolina State University Award Details The researchers in this project will study fully data-driven systems to provide both scalable and individualized support for learners. Open-ended, media-rich visual programming environments such as Scratch and Snap represent the next-generation genre for engaging and inspiring students to learn programming. However, solving […]
EAGER: Exploiting Keystroke Logging and Eye-Tracking to Support the Learning of Writing
PIs: Evgeny Chukharev-Khudilaynen, James Ranalli Iowa State University Award Details Learning how to write and communicate well is one of the core challenges for becoming a productive member of society, and much is known about the psychology of the writing process. Yet, most writing instruction focuses instead on the product of writing, with limited ability […]
EAGER: Collaborative Research: Virtual STEM Buddies for Personalized Learning Experiences in Free Choice Informal Learning Settings
PIs: Kyle Johnsen, University of Georgia Research Foundation (Award Details) Karen Kelly, The Children’s Museum of Atlanta (Award Details) Elizabeth DiSalvo, Georgia Tech Research Corporation (Award Details) This project investigates how to provide customized instructional scaffolding to young kids to learn science in unstructured, out-of-school environments. The innovation is in using ‘virtual STEM buddies’ (VSBs), […]
EXP: Helping Teachers Help Their Students: Teachers’ Use of Intelligent Tutoring Software Analytics to Improve Student Learning.
PIs: Vincent Aleven, Bruce McLaren Carnegie-Mellon University Award Details Improving learning in K-12 Science, Technology, Engineering, and Mathematics (STEM) is a critical national need as more jobs require STEM proficiency. Recently, Intelligent Tutoring Systems (ITSs) have shown great promise in improving STEM learning in middle school and high school. While these tutors support students directly, […]
EAGER: Computational Models of Essay Rewritings
PIs: Rebecca Hwa, Diane Litman University of Pittsburgh Award Details Natural language processing (NLP) is an integral part of an intelligent tutoring system for writing; it allows the system to automatically analyze student writings and provide feedback to help students to learn. For example, methods have been developed to automatically detect and correct grammar usage […]
EXP: Partners in Learning: Building Rapport with a Virtual Peer Tutor
PIs: Justine Cassell, Louis-Philippe Morency, Amy Ogan Carnegie-Mellon University Award Details This project seeks to understand, and capitalize on, how teachers or tutors build rapport with learners by building technologies that support rapport. Research will study what rapport with learners looks like, when students deploy rapport techniques, when and how deploying rapport techniques (whether by […]
EXP: Collaborative Research: PerSketchTivity – Empowering and Inspiring Creative, Competent, Communicative, and Effective Engineers through Perspective Sketching
PIs: Julie Linsey and Wayne Li, Georgia Tech (Award Details) Jeffery Liew and Erin McTigue, Texas A&M (Award Details) This project examines whether technology can support learning to freehand sketch. Sketching has been demonstrated to play an important role in a number of domains, including engineering, and the ability to quickly sketch has been shown […]
DIP: Teaching Writing and Argumentation with AI-Supported Diagramming and Peer Review
PIs: Kevin Ashley, Diane Litman, Christian Schunn University of Pittsburgh Award Details The PIs are investigating the design of intelligent tutoring systems (ITSs) that are aimed at learning in unstructured domains. Such systems are not able to do as much automatically as ITSs working in traditionally narrow and well-structured domains, but rather they need to […]
EXP: Developing a Tutor to Guide Students as they Invent Deep Principles with Contrasting Cases
PI: Catherine Chase Teachers College, Columbia University Award Details This is a project to develop a tutor that will teach the skills of innovation through invention. The Invention Tutor will simulate the guidance of a well-trained inquiry teacher, who asks critical questions and gives feedback just at the right time, to push students’ thinking forward. […]