Assessing Writing Jan 2026 Open Access

Generative artificial intelligence for automated essay scoring: Exploring teacher agency through an ecological perspective

Jessie S. Barrot National University

Abstract

Generative artificial intelligence (AI) is increasingly used in writing assessment, particularly for automated essay scoring (AES) and for generating formative feedback within automated writing evaluation (AWE). While AI-driven AES enhances efficiency and consistency, concerns regarding accuracy, bias, and ethical implications raise critical questions about its role in assessment. This paper examines the impact of generative AI on teacher agency through an ecological perspective, which considers agency as shaped by personal, institutional, and sociocultural factors. The analysis highlights the need for teachers to critically mediate AI-generated scores and feedback to align them with pedagogical goals, ensuring AI functions as an assistive tool rather than a determinant of assessment outcomes. Although AI can streamline assessment, over-reliance risks diminishing teachers’ evaluative expertise and reinforcing biases embedded in AI systems. Ethical concerns, including transparency, data privacy, and fairness, further complicate its adoption. To address these challenges, this paper proposes a framework for responsible AI integration that prioritizes bias mitigation, data security, and teacher-driven decision-making. The discussion concludes with pedagogical implications and directions for future research on AI-assisted writing assessment. • Teachers can actively mediate AI-generated scores to maintain agency. • Dependence on AES may weaken teachers’ evaluative skills. • Bias, data privacy, and AI opacity can undermine teachers’ decision-making. • AI literacy and hybrid assessment models can promote teacher autonomy. • A framework for protecting teacher agency in generative AI–based AWE is presented.

Journal
Assessing Writing
Published
2026-01-01
DOI
10.1016/j.asw.2025.100990
CompPile
Open Access
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Citation context

Cited by in this index (2)

  1. Xu et al. (2026)
    Re-centering the role of humans in AI-assisted writing scoring: A scoping revie…
    Assessing Writing
  2. Wilson et al. (2026)
    AI and writing assessment: Innovations, validity, and ethical considerations
    Assessing Writing

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