Analyzing the impact of structure in handwriting recognition software
Author(s)
Chao, Neil E![Thumbnail](/bitstream/handle/1721.1/66405/755081797-MIT.pdf.jpg?sequence=5&isAllowed=y)
DownloadFull printable version (9.723Mb)
Other Contributors
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Kimberle Koile.
Terms of use
Metadata
Show full item recordAbstract
Handwriting recognition for text and numbers has existed for Tablet PCs and specialty devices for almost a decade. The use of such software in a classroom can shorten the latency between answers to exercises and teacher feedback. While text and number inputs have already been well explored, graphical examples and math problems are a relatively new territory for recognition software. Under the guidance of the NSFfunded INK-12 Project, I explored the impact of structure on the ability of Ink-Analysis Handwriting Recognition to understand students' solutions math and science exercises, hoping to find the ideal balance between accurate grading and minimal human effort. I tested a prototype system aimed at supporinting "virtual-teacher-guided" learning in elementary school classrooms in the Greater Boston area.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 95-96).
Date issued
2011Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer SciencePublisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.