The impact of AI-driven tools on student writing development: A case study

Raigul Zheldibayeva 1 2 * , Ana Karina de O. Nascimento 2 3, Vania Castro 2, Mary Kalantzis 2, Bill Cope 2
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1 Zhetysu University named after Ilyas Zhansugurov, Taldykorgan, KAZAKHSTAN
2 University of Illinois Urbana-Champaign, Champaign, IL, USA
3 Universidade Federal de Sergipe, São Cristóvão, BRAZIL
* Corresponding Author
Online Journal of Communication and Media Technologies, Volume 15, Issue 3, Article No: e202526. https://doi.org/10.30935/ojcmt/16738
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ABSTRACT

This paper aims to examine the impact of the CGScholar (Common Ground Scholar) Artificial Intelligence (AI) Helper on a pilot research initiative involving the writing development of 11th-grade students in English Language Arts. CGScholar AI Helper is an evolving and innovative web-based application designed to support students in their writing tasks by providing specified AI-generated feedback. This is a case study and relates to one of six interventions, involving one teacher and six students in a diverse school. A qualitative thematic approach to data analysis is employed, combining data from students’ initial and reviewed writing assignments, selected focus group feedback, teacher’s post-survey, and the research team’s observations. It explores to what extent customized AI-driven feedback can support students’ writing development. The findings suggest that the implementation of AI helper supported the development of students’ writing in several ways. Therefore, researchers conclude AI can be helpful in K-12 writing considering how it is calibrated to serve the teacher’s teaching objectives. The research also elicited suggestions from the teacher and students about ways of improving the still in development tool, which it is recommended to be taken into consideration.

CITATION

Zheldibayeva, R., Nascimento, A. K. D. O., Castro, V., Kalantzis, M., & Cope, B. (2025). The impact of AI-driven tools on student writing development: A case study. Online Journal of Communication and Media Technologies, 15(3), e202526. https://doi.org/10.30935/ojcmt/16738

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