AI-based Self-reading Platform
Authors: Renuka Bhagat, Kunal Gunjal, Aditi Khoje, Pooja Datkhile
Country: India
Full-text Research PDF File:
View |
Download
Abstract: Designing a collaborative reading annotation tool with functionalities for annotating a digital English article can accumulate and share the knowledge of readers who participate in reading learning processes in a web-based learning environment. The annotated content helps new readers understand articles and helps readers who have read an article obtain a deeper and broader understanding than when reading digital article without annotations. However, the self-regulated learning ability of individual learner on reading learning materials and contributing reading annotations becomes a key factor affecting learning performance of collaborative reading annotation. Thus, this work proposes a self-regulated learning assisted mechanism in a collaborative reading annotation system which can promote learners’ reading annotation abilities in order to facilitate more high quality reading annotations generated by learners during performing reading annotation processes. We are creating a web application which will be used by user to read the phrases and system will process it according to the trained data, system will also give notification to user which word is not yet completed with correct pronunciation.
Keywords: Machine Learning, Self-learning, Self-learning Mechanism, Authentication
Paper Id: 230136
Published On: 2023-05-19
Published In: Volume 11, Issue 3, May-June 2023
Cite This: AI-based Self-reading Platform - Renuka Bhagat, Kunal Gunjal, Aditi Khoje, Pooja Datkhile - IJIRMPS Volume 11, Issue 3, May-June 2023.