Work

Use of AI-assisted writing tools for student self-assessment at school: survey on teachers’ perceptions and practices

Year: 2026

Type: article

Abstract: Writing is a complex, learned skill that requires continuous practice and support. Digital technologies, and more recently AI-assisted writing tools, have been introduced to enhance students’ writing and self-assessment, with potential benefits for motivation, accuracy, and collaboration. Their effectiveness, however, depends on how they are integrated into educational contexts and on teachers’ perceptions. This exploratory study, conducted between February and April 2025 with n. 1,072 pre-service teachers enrolled in qualification programs in Italy, examines perceptions and practices related to AI-assisted writing tools for student self-assessment. In this study, the construct was operationalised through a restricted set of widely used AI-based generative writing tools available at the time of data collection. Adopting a mixed embedded design that combines quantitative and qualitative analyses, the research found that most teachers expressed cautious or sceptical views about their general usefulness, yet more positive attitudes emerged toward specific tools (e.g., ChatGPT) and sub-skills, especially spelling and text composition. Qualitative data indicated that teachers who experimented with such tools perceived benefits for student motivation, engagement, and skill development, though concerns persisted regarding critical thinking and over-reliance on algorithms. The findings underscore the need for targeted teacher training and further research to support the effective pedagogical integration of AI-assisted tools in writing instruction.

Source: Frontiers in Education

DOI: 10.3389/feduc.2026.1701597

Authors: Laura Sara Agrati, Viviana Vinci, Arianna Beri, Pierangelo Berardi

Institutions: Pegaso University, University of Foggia, University of Bergamo

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $2,353