9/1/18-8/31/21 PIs: Carolyn Rose, Carnegie-Mellon University (Award Details) Jason Levin, Western Governors University (Award Details) The employment landscape is changing and expanding, creating uncertainty as individuals navigate decisions regarding career preparation and continuing education. This project develops technology to provide guidance for college students to access high quality information and guidance within a large and […]
Category Archives: CFLT-WHTF
Collaborative Research: Multimodal Affective Pedagogical Agents for Different Types of Learners
8/1/18-7/31/21 PIs: Nicoletta Adamo-Villani, Purdue University (Award Details) Richard Mayer, University of California-Santa Barbara (Award Details) While most research on embodied pedagogical agents (adaptive virtual agents that guide and mentor learners) explores cognitive features, this project investigates the role of agent affect/emotion. This project examines how the agent’s affective state (e.g., seeming interested or concerned) […]
Collaborative Research: Teaching Human Motion Tasks at Population Scale
9/15/18-8/31/21 PIs: Devin Balkcom, Dartmouth College (Award Details) Weifu Wang, SUNY at Albany. (Award Details) The project will develop technology and study methods for teaching motion tasks, with the teaching of sign language as a first application. Simultaneous placement or quick movement of parts of the body is hard to observe, explain, and execute. While […]
Cyberlearning: Sensei: High-Fidelity, Non-Invasive Classroom Sensing for Professional Development
9/1/18-8/31/21 PIs: Amy Ogan, Yuvraj Agarwal, Christopher Harrison Carnegie-Mellon University Award Details For years, research has shown that moving away from large lectures and increasing student engagement and participation in classrooms significantly improves learning. Unfortunately, professors lack quality professional development opportunities to improve their instruction, and typically receive no training on how to teach. This […]
Putting Teachers in the Driver’s Seat: Using Machine Learning to Personalize Interactions with Students (DRIVER-SEAT)
9/1/18-8/31/21 PIs: Anthony Botelho, Neil Heffernan, Jacob Whitehill, Korinn Ostrow Worcester Polytechnic Institute Award Details This is a project that will use machine learning to personalize messages about student homework. The project will apply technologies used by Google’s Smart Reply, a functionality that uses machine learning to generate and suggest human-like email responses, to provide […]
ROBO-VI: A Virtual-Internship-Based Hybrid Learning Technology to Prepare Traditional and Non-Traditional Students to Work with Collaborative Robots
8/15/18-7/31/21 PIs: Bilge Mutlu, Andrew Ruis, David Shaffer University of Wisconsin-Madison Award Details Collaborative robots are emerging as a new family of advanced technologies that are designed to work side-by-side with people in industrial settings. These robots can improve the productivity and flexibility in manufacturing and logistics industries, while also assisting workers in repetitive, and […]
Leverage Augmented Reality for Safety Education in the Logistics Industry
9/1/18-8/31/21 PIs: PI: Xu Xu, Karen Chen, Tianfu Wu, Jing Feng North Carolina State University Award Details he project will design and research an immersive and personalized education approach by leveraging augmented reality (AR) to support workers’ understanding of risk factors associated with their work, and encourage workers to perform tasks using appropriate body motion. […]
Human/AI Co-Orchestration of Dynamically-Differentiated Collaborative Classrooms
9/1/18-8/31/21 PIs: Vincent Aleven, Nikol Rummel Carnegie-Mellon University Award Details This project will create and demonstrate new technology that supports dynamically-differentiated instruction for the classroom of the future. This new vision centers on carefully-designed partnerships between teachers, students, and artificial intelligence (AI). AI-powered learning software will support students during problem-solving practice, providing either individual guidance […]
Collaborative Research: CSEdPad: Investigating and Scaffolding Students’ Mental Models during Computer Programming Tasks to Improve Learning, Engagement, and Retention
9/1/18-8/31/21 PIs: Peter Brusilovsky University of Pittsburgh (Award Details) Vasile Rus, University of Memphis (Award Details) Computing skills, such as computer programming, are an integral part of many disciplines, including the fields of science, technology, engineering, and math (STEM). Although such skills are in high-demand, and the number of aspiring Computer Science (CS) students is […]