| dc.contributor.advisor | Kimberle Koile. | en_US |
| dc.contributor.author | Chao, Neil E | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2011-10-17T21:22:21Z | |
| dc.date.available | 2011-10-17T21:22:21Z | |
| dc.date.copyright | 2011 | en_US |
| dc.date.issued | 2011 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/66405 | |
| dc.description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. | en_US |
| dc.description | Cataloged from PDF version of thesis. | en_US |
| dc.description | Includes bibliographical references (p. 95-96). | en_US |
| dc.description.abstract | 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. | en_US |
| dc.description.statementofresponsibility | by Neil E. Chao. | en_US |
| dc.format.extent | 131 p. | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
permission. See provided URL for inquiries about permission. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | Analyzing the impact of structure in handwriting recognition software | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | M.Eng. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| dc.identifier.oclc | 755081797 | en_US |
