A Moodle Plugin for Handwritten Answer Input, Management, and Recognition Supporting Japanese, English, Mathematical, and Chemical Formulas

This study presents the development of a Moodle plugin that integrates a web-based handwriting input interface with handwriting-to-text recognition, supporting handwritten input in Japanese, English, and mathematical and chemical formulas. Although computer-based learning systems are widely used in education, they predominantly emphasize multiple-choice or short-answer question types that require conventional keyboard and mouse input. Conversely, structured responses, such as mathematical and chemical expressions, often require specialized input methods, such as LaTeX and Equation Editor, which are challenging for many learners to use. To address these limitations, we developed a Moodle plugin that provides an intuitive and cognitively efficient handwriting-based input interface. The plugin enables learners to produce handwritten responses naturally while preserving raw handwriting data and recognition texts to support transparent scoring. This study bridges the gap between traditional pencil-and-paper assessments and contemporary digital learning environments. It also enhances the authenticity and interactivity of assessments conducted within Moodle. In particular, this paper describes the architecture of the plugin, implementation, and integration challenges encountered within the Moodle system. Usability testing results indicate the plugin can enhance learner engagement and assessment accuracy, representing a step toward personalized and interactive digital education.