Keyword: writing

ABSTRACT: The emergence of ChatGPT has stimulated interest in its application to second language writing in higher education. While previous studies have compared ChatGPT feedback with that of teachers and examined student engagement with automated, teacher, and peer feedback, little attention has been paid to student engagement specifically with ChatGPT feedback. This study explores student engagement with both ChatGPT and teacher feedback in a college EFL (English as foreign language) argumentative writing class. The participants were 46 second-year English majors who completed two writing tasks. One essay received feedback from ChatGPT, generated with prompts related to both content and language, while the other received teacher feedback. Students revised their essays based on these two feedback types. Analysis of students’ revisions, questionnaire responses, and interview data indicated that students actively engaged with both forms of feedback. Interviews further revealed that students found both ChatGPT and teacher feedback to be understandable and acceptable. In light of these findings, the study suggests that teachers can effectively integrate ChatGPT feedback into teacher feedback in L2 writing classrooms to enhance student engagement and writing proficiency.

ABSTRACT: The integration of AI technologies into the writing process has significantly altered traditional notions of authorship, creativity, and intellectual labor. Historically, writing was seen as a human-driven cognitive and creative exercise, but with the rise of generative AI tools such as ChatGPT and Claude, the line between human and AI contributions has become increasingly ambiguous. This paper addresses the limitations of the current sliding scale model, which views AI involvement as ranging from “none” to “complete”. In its place, we propose a new multidimensional framework that more accurately reflects the complexity of human-AI collaboration in writing. The model includes axes for content generation, structural assistance, creative input, and analytical contribution, emphasizing the varying degrees of interaction between human writers and AI tools. This framework highlights how AI can assist in different aspects of writing without fully replacing human agency, while also underscoring the importance of ethical and intellectual accountability. By providing a more comprehensive understanding of the collaborative dynamics between humans and AI, this paper offers a foundation for future research into optimizing these interactions in creative and academic contexts.

ABSTRACT: Automated writing evaluation systems are formative assessment systems that provide immediate, automated feedback on L1, L2, and EFL students’ writing in the form of writing quality scores and suggestions for revising. As such, these systems have the potential for alleviating some of the persistent barriers teachers face to implementing evidence-based writing instruction practices. However, simply adopting this technology without careful attention to how it is implemented will not guarantee instructional benefits. In this article, we draw on prior research to make recommendations to effectively integrate automated writing evaluation alongside evidence-based writing instruction practices to improve writing instruction and intervention, leveraging the affordances of this technology while addressing its limitations. Specifically, we discuss how researchers, interventionists, and educators using automated writing evaluation should develop students’ knowledge of underlying evaluation criteria; teach strategies for planning, drafting, and revising; supplement automated feedback with effective teacher-provided feedback; and enact goal setting and progress monitoring.

ABSTRACT: In the rapidly evolving landscape of English composition education, the integration of AI writing tools like ChatGPT and Claude 2.0 has marked a significant shift in pedagogical practices. A mixed-method study conducted in Fall 2023 across three sections, including one English Composition I and two English Composition II courses, provides insightful revelations. The study, comprising 28 student respondents, delved into the impact of AI tools through surveys, analysis of writing artifacts, and a best practices guide developed by an honors student. Initially, the study observed a notable anxiety and mistrust among students regarding the use of AI in writing. However, this apprehension gradually subsided as students increasingly integrated these tools into their writing processes, indicating a shift from skepticism to practical application. The analysis of writing artifacts, particularly early drafts, revealed distinct patterns of AI tool usage, differentiating between students utilizing the tools effectively and those attempting to shortcut the writing process. The final papers, while not overtly indicating AI usage, demonstrated nuanced integration of AI in iterative and recursive tasks like refining arguments and developing ideas at the paragraph level. This suggests a trend toward a hybrid model of writing instruction, where traditional methods are complemented by strategic use of emergent technologies. The study underscores the importance of revised instructional strategies that blend conventional writing techniques with guidance on effective and ethical AI tool usage. It highlights the potential of AI tools in supporting the writing process while also cautioning against over-reliance. The findings of this study offer valuable insights for educators and institutions aiming to develop a balanced and effective hybrid writing instruction model, catering to the needs of contemporary English composition classrooms while maintaining academic integrity.