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PhD Thesis Proposal

December

9
Tue
Jennifer Cross Carnegie Mellon University
Tuesday, December 9
12:00 pm to 12:00 am
Creative Robotic Systems for Talent-Based Learning

Event Location: GHC 4405

Abstract: In recent years, the U.S. educational system has fallen short in training the technology innovators of the future. To do so, we must give students the experience of designing and creating technological artifacts, rather than relegating students to the role of technology consumers, and must provide students with engineering activities that correspond to their interests and talents. Educational robotics systems are one possible method for providing students with these opportunities and experiences.

Our creative robotics program, Arts & Bots, combines craft materials with robotic construction and programming tasks in a manner that encourages complexity such that a wide variety of student interests can surface. Prior work has indicated that Arts & Bots projects improve student understanding of systems engineering concepts and improve student confidence as technology creators.

Our proposed work is focused on further developing Arts & Bots as a tool for talent-based learning, which we define as leveraging understanding of a student’s interests and existing talent areas to encourage and motivate learning. This thesis outlines two work thrusts:

1. Teacher-focused Thrust – We will collect and analyze data on current classroom implementations and teacher professional development. Following this analysis, we will refine the teacher-training model and develop new resources to prepare teachers to implement a creative robotics program with an emphasis on the identification and cultivation of diverse student talents and interests.

2. Design-focused Thrust – We will analyze existing educational robotics systems to identify common and distinguishing features which support different student talents and interests. Additionally, we will develop a taxonomy of novice-generated Arts & Bots robots in order to identify those system features and affordances that are beneficial for talent-based learning. From this taxonomy, we will develop design recommendations for educational robotics systems and prototype improvements to the Art & Bots system.

Committee:Illah Nourbakhsh, Chair
Jack Mostow
Aaron Steinfeld
Mitchel Resnick, MIT, Media Lab