Constructing an AI-Enhanced Teacher-Student Collaborative Assessment Model for High School English Continuation Writing

Mingliang Liu

doi:10.63313/IJED.9063

Authors

Mingliang Liu China West Normal University, China Author

DOI:

https://doi.org/10.63313/IJED.9063

Keywords:

AI-enhanced assessment, teacher-student collaborative assessment (TSCA), continuation writing, writing anxiety, cognitive load theory, affective filter hypothesis

Abstract

Continuation writing has become a high-stakes task in China’s national college entrance examination (Gaokao), yet students frequently experience heightened writing anxiety and struggle with linguistic accuracy and content coherence. Traditional teacher-centered assessment approaches are often time-intensive and insufficiently responsive, limiting opportunities for meaningful feedback and student engagement. To address these challenges, this paper proposes a theoretically grounded, AI-enhanced Teacher-Student Collaborative Assessment (TSCA) model tailored for high school English continuation writing. Drawing on Cognitive Load Theory (Sweller, 1988) and Krashen’s (1981) Affective Filter Hypothesis, the model reconceptualizes the roles of artificial intelligence and human agents: AI performs automated correction of low-level linguistic errors (extraneous cognitive load), thereby enabling teachers and students to collaboratively focus on higher-order dimensions such as narrative coherence, stylistic alignment, and thematic development. The proposed framework features a four-stage cyclical process— (1) AI-assisted text analysis, (2) AI-mediated initial feedback, (3) teacher-student co-evaluation, and (4) student-driven revision—which aims to simultaneously reduce writing anxiety through non-judgmental automated feedback and enhance writing quality via structured pedagogical dialogue. While empirical validation remains future work, this theoretical model presents a feasible and integrative pathway for leveraging AI not as a replacement for teachers, but as a cognitive and affective scaffold that supports more equitable, efficient, and human-centered writing instruction in the digital era.

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