AI-Enhanced Writing Self- Assessment Empowering Student Revision with AI Tools

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Lesson PDF Lesson DOCX Student Guide AI Prompts 4-Step Process Peer-Review Worksheet
Published: Dec 10, 2024
DOI: https://doi.org/10.13001/jtilt.v3i2.9119
Keywords:
Writing Self-Assessment, AI-Enhanced Rubrics, Revision Strategies, Peer-Review

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Robin Dazzeo
University of Hawai'i at Mānoa
https://orcid.org/0000-0003-4070-1402

Abstract

This technology-rich, three-day lesson for 9th-12th grade English Language Arts students leverages artificial intelligence (AI)-enhanced rubrics and writing analysis tools (Ouyang & Jiao, 2021) to improve student writing and self-assessment skills. Students explore AI-enhanced digital rubrics, use AI tools to analyze their writing, and apply AI-generated feedback to revise their work. This approach enhances current writing assignments and develops critical thinking skills and digital literacy. Assessments include AI-generated feedback reports, peer evaluations, and final revised writing samples demonstrating improvement based on AI and peer input, equipping students with valuable skills for future writing tasks.

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Article Details

How to Cite
Dazzeo, R. (2024). AI-Enhanced Writing Self- Assessment : Empowering Student Revision with AI Tools. Journal of Technology-Integrated Lessons and Teaching, 3(2), 80–85. https://doi.org/10.13001/jtilt.v3i2.9119
Issue
Vol. 3 No. 2 (2024): Journal of Technology-Integrated Lessons and Teaching
Section
JTILT Competitions
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Author Biography

Robin Dazzeo, University of Hawai'i at Mānoa

Robin Dazzeo is an instructor in the Special Education department and doctoral student in Learning Design and Technology at the University of Hawaii at Manoa, where she teaches preservice special education teacher candidates. As a dual-licensed secondary English Language Arts and Special Education teacher, she brings classroom expertise to her research on integrating artificial intelligence in K-12 education. Her work focuses on developing AI-enhanced assessment tools and digital learning supports through the Universal Design for Learning framework. Her research interests explore the intersection of special education and emerging technologies, emphasizing the creation of inclusive, technology-rich learning environments that promote student self-assessment and academic achievement.