Gamifying Math Education using Object Detection
This work addresses the problem of improving math education through interactive technology for young children, though it is incremental in applying existing object detection methods to a specific educational context.
The paper tackles the challenge of oriented object detection for densely packed shape tiles in a geometry learning system for children aged 5-8, achieving real-time performance with high precision and recall on consumer devices.
Manipulatives used in the right way help improve mathematical concepts leading to better learning outcomes. In this paper, we present a phygital (physical + digital) curriculum inspired teaching system for kids aged 5-8 to learn geometry using shape tile manipulatives. Combining smaller shapes to form larger ones is an important skill kids learn early on which requires shape tiles to be placed close to each other in the play area. This introduces a challenge of oriented object detection for densely packed objects with arbitrary orientations. Leveraging simulated data for neural network training and light-weight mobile architectures, we enable our system to understand user interactions and provide real-time audiovisual feedback. Experimental results show that our network runs real-time with high precision/recall on consumer devices, thereby providing a consistent and enjoyable learning experience.