Assessing handwriting skills in a web browser: Development and validation of an automated online test in Japanese Kanji.

ABSTRACT: Online language and literacy assessments have become prevalent in research and practice across settings. However, a notable exception is the assessment of handwriting and spelling, which has traditionally been conducted in person with paper and pencil. In light of this, we developed an automated, browser-based handwriting test application (Online Assessment of Handwriting and Spelling: OAHaS) for Japanese Kanji (Study 1) and examined its psychometric properties (Study 2). The automated scoring function using convolutional neural network (CNN) models achieved high recall (98.7%) and specificity (84.4%), as well as high agreement with manual scoring (95.4%). Additionally, behavioral validation with data from primary school children (N = 261, 49.0% female, age range = 6-12 years) indicated th

SUBMITTER: Inoue T 

PROVIDER: S-EPMC11685258 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature