Easye: A digital learning platform for beginner’s writing companion with feedback analysis
By: Cunanan, Eldwin Emmanuel T.; Franco, Ma. Francheska L.; Gulapa, Kate Ysabelle I
Language: English Publisher: . . c2025Content type: text Media type: unmediated Carrier type: volumeGenre/Form: academic writingDDC classification: . LOC classification: T58.6 C86 2025| Item type | Current location | Home library | Collection | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|---|
| Thesis/Dissertation | PLM | PLM Filipiniana Section | Filipiniana-Thesis | T58.6 C86 2025 (Browse shelf) | Available | FT8774 |
Browsing PLM Shelves , Shelving location: Filipiniana Section , Collection code: Filipiniana-Thesis Close shelf browser
ABSTRACT: In today’s digital era, many young learners and individuals with literacy challenges struggle to acquire basic writing skills due to traditional teaching methods that fail to sustain engagement and adapt to diverse learning needs. This study addresses the critical need for an innovative, accessible, interactive educational tool to enhance handwriting proficiency. The main objective of the research is to design and develop EasyE, a digital learning platform designed for young learners. The platform integrates machine learning for handwriting recognition, a feedback analysis system, and a progress tracking feature with engaging tasks to support skill improvement. To address this, the researchers design and develop EasyE, an intuitive digital learning platform that serves as a writing companion designed to the user’s needs. EasyE incorporates Optical Character Recognition (OCR) to convert handwritten input into digital data, optimizing data entry and enabling immediate and meaningful feedback. Demonstrated using Julyter Lab, the OCR system not only needs handwritten characters but also assesses handwritten quality for comprehensive evaluation. The platform’s feedback analysis feature, implemented in Visual Studio Code, evaluates writing accuracy through a scoring system that examines individual strokes and overall character formation. Additionally, EasyE, integrates recursive algorithms to deconstruct complex learning tasks into manageable steps, creating a personalized, gradually intensifying learning experience that maintains user engagement without causing cognitive overload. As a result, EasyE successfully combines advanced technologies to support learners at every stage of their writing journey, with testing showing notable improvements in writing quality, user engagement, and motivation, highlighting its potential as an effective educational tool. Incorporating interactive digital platforms like EasyE can significantly enhance early writing development and support literacy education through adaptive and engaging methods.
Filipiniana

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