Artificial Intelligence Vs. Human Feedback in L2 Academic Writing: a Systematic Review

Abstract Book of the 10th International Conference on Teaching, Learning and Education

Year: 2025

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Artificial Intelligence Vs. Human Feedback in L2 Academic Writing: a Systematic Review

Mabel Ortiz, Claudio Diaz Larenas

ABSTRACT:

This systematic review examines recent empirical studies comparing artificial intelligence (AI)-generated feedback and human feedback in the context of academic writing in English as a second language (L2). With the growing integration of AI tools such as ChatGPT and Google Geminis, into writing instruction, there is a need to understand their effectiveness and how students perceive their use in comparison to traditional teacher feedback.
The review follows PRISMA guidelines and includes studies published between 2018 and 2025 retrieved from databases such as Scopus, ERIC, and Web of Science. Inclusion criteria focus on peer-reviewed empirical research comparing AI and human feedback in higher education contexts. Thematic synthesis was used to analyze findings across studies.
Preliminary results indicate that while AI feedback often enhances accuracy in grammar and vocabulary, human feedback is consistently valued for its depth, contextual relevance, and affective support. Moreover, students’ perceptions tend to favor a blended approach that combines the immediacy of AI with the personalized guidance of teacher feedback. This review identifies emerging trends, gaps in the literature, and practical implications for feedback practices in L2 writing instruction.

Keywords: Academic Writing, Artificial Intelligence, Feedback, L2 Writing, Systematic Review