We will develop a system both for training efficient handwriting in school children and for scientific testing of hypotheses on handwriting education. Handwriting is the only and most widely learned fine motor skill. The US school system spends $200M per year (our estimate) on handwriting instruction materials. Teachers receive only limited training to teach handwriting and the curriculum permits only limited time for handwriting instruction. Yet, little is known how to improve quality and time efficiently of handwriting instruction. To satisfy the demand for scientific support of handwriting instruction, we are developing the """"""""WritAlyzeR"""""""" software. This software can work autonomously during the normal lessons of the class. Therefore, the handwriting learning data collected will be more representative than previous automatic handwriting instruction systems where a teacher or experimenter monitors and influences the children. The WritAlyzeR enables researchers to conduct research on handwriting instruction in a very time saving manner. The WritAlyzeR, in combination with our existing MovAlyzeR will form a powerful research tool to test many hypotheses on improving handwriting teaching methods. We will market the WritAlyzeR as a computer-aided instruction system and also provide it as a free extension to all researchers who purchased MovAlyzeR licenses so that many more research groups will be able to find ways to improve handwriting instruction in a concerted effort. This will eventually yield improved handwriting instruction methods for primary school education. The WritAlyzeR uses a simple procedure to teach children handwriting. First the child will see an example of the writing exercise as a real-time movement on the PC display. Subsequently, the student will try to perform the writing movement. The movement will be recorded using a low-cost digitizer made for the educational market for less than $200. A digitizer consists of a small tablet and an electronic pen which enables high-precision (0.01 cm) recording of the position of the pen tip at a high sampling rate (100 Hz), thus accurately capturing movements of the pen tip on and above the tablet. The recorded movement will be processed on the PC and presented on the display in real-time. Color coding of the strokes will show where the child used abnormal forces. In addition, a cumulative fluency score will be presented which increases while the child keeps improving movement fluency. As a reward, the child can play briefly on a novel computer game which requires fluent movements to succeed. In this proposal three of the many possible hypotheses will be tested. Does varying writing size help to obtain optimal hand posture and pen grip and eventually more efficient writing? Does preplanning the target point of each stroke accelerate learning? Does real-time sound feedback during writing indicating dysfluencies help to improve fluency? R44 HD 43576 """"""""Handwriting Teaching Tool"""""""" 12/23/2005 5:57 PM Narrative Handwriting instruction is needed to produce efficient and legible handwriting. This will remain important since students lacking handwriting proficiency will be disadvantaged in taking lecture notes or writing exams. Teachers have insufficient training and time to teach handwriting and refer many students to occupational therapists taking away time to treat students with motor control problems. As a consequence, after-school handwriting instruction for children is in demand. Illegible or slow handwriting causes too low grades barring students from continued education. Handwriting re-education is also in demand in health care. Illegible handwriting by physicians causes 10% of the prescriptions to be misread causing preventable medication errors. ? ? ?

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
Project #
2R44HD043576-02A1
Application #
7273826
Study Section
Special Emphasis Panel (ZRG1-BBBP-B (10))
Program Officer
Miller, Brett
Project Start
2004-08-16
Project End
2009-08-31
Budget Start
2007-09-15
Budget End
2008-08-31
Support Year
2
Fiscal Year
2007
Total Cost
$379,663
Indirect Cost
Name
Neuroscript, LLC
Department
Type
DUNS #
098854966
City
Tempe
State
AZ
Country
United States
Zip Code
85282