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Документ Developing Writing Competence Among Pre-Service EFL Teachers Using AI Tools(2026) Podosynnikova Hanna Ihorivna; Подосиннікова Ганна Ігорівна; V. V. Homolia; В. В. ГомоляThe article provides an overview of how artificial intelligence (AI) can be applied to develop writing competence among English as a foreign language (EFL) pre-service teachers, while considering the ethical and legal implications of introducing AI in the learning environment. AI’s impact is regarded in terms of its influence on both writing competence and writing performance, including grammar, vocabulary, language retention duration, and its processing depth, as well as sentence structure, text organisation, and narrative development. The authors investigate the opportunities and threats of AI-driven learning environments, specifically the accommodation of diverse students’ needs and preferences, language accuracy enhancement, and the decline in student involvement concurrent with lower critical thinking skills. Both strengths and weaknesses of AI in assisting writing instruction are studied, including immediate input processing and versatile output generation, accurate language use and correction, artificiality, unreliability, and lack of metalingual knowledge. The research also examines the expediency of generating writing materials, including language scaffolds, models, reference materials, and stimulus materials. General large language models and specialised AI tools are explored as a way to facilitate dialogic writing, overcoming organisational problems and matching students’ language proficiency and motivation levels. Involving students in the creation of engaging writing assignments, offering real-life-based tasks that incorporate AI-proof media, process assessment, and oral assessment during writing conferences, is viewed as a way to maintain students’ involvement and ensure that AI tools enhance not only writing performance but also writing competence. AI-generated feedback and assessment are examined in terms of efficiency, accuracy, tone, and context sensitivity. The authors claim that explicit instruction is a prerequisite for efficient prompting and post-editing, combined with a critical evaluation of AI output.