Article: Artificial intelligence-enhanced Chinese academic writing instruction for cross-cultural communication: a framework for Sino-French and Sino-African contexts Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.92 pp.25 - 59 Abstract: Recent advances in artificial intelligence (AI) have enabled automated support for academic writing; however, many platforms remain 'tool-centric', providing isolated corrections rather than process-aware instructional support. This paper proposes a novel AI-enhanced academic writing instruction platform designed from an ICT perspective, focusing on the specific rhetorical needs of Sino-French and Sino-African cross-cultural academic communication. The framework integrates a three-layer architecture: a multi-level linguistic feature extraction layer using fine-tuned transformer models, a learner modelling layer driven by longitudinal data analytics, and an adaptive feedback engine. To validate the system, a 16-week empirical study was conducted with 342 undergraduate students. Analysis of a corpus comprising 1,250 academic essays reveals that the platform significantly enhances discourse coherence (18.4% improvement) and lexical complexity (12.6% increase) compared to traditional automated writing evaluation tools. Statistical significance was confirmed via a paired-sample t-test (<i>p</i> < 0.01), and effect size calculations (Cohen's <i>d</i> = 0.76) suggest a robust impact on student writing quality. The results demonstrate that embedding evaluation directly into the system operation enables a continuous feedback loop that fosters long-term linguistic development in specialised academic contexts. Inderscience Publishers - linking academia, business and industry through research

Title: Artificial intelligence-enhanced Chinese academic writing instruction for cross-cultural communication: a framework for Sino-French and Sino-African contexts

Authors: Yan Xiao; Yunbiao Xu; Yanxia Gong

Addresses: College of Liberal Arts, Hunan Normal University, Changsha, Hunan, 410081, China; College of Humanities, Hunan City University, Yiyang, Hunan, 413000, China ' College of Information Engineering, Hunan Industry Polytechnic, Changsha, Hunan, 410000, China ' School of Humanities and Media Communications, Changsha Medical University, Changsha, Hunan, 410081, China

Abstract: Recent advances in artificial intelligence (AI) have enabled automated support for academic writing; however, many platforms remain 'tool-centric', providing isolated corrections rather than process-aware instructional support. This paper proposes a novel AI-enhanced academic writing instruction platform designed from an ICT perspective, focusing on the specific rhetorical needs of Sino-French and Sino-African cross-cultural academic communication. The framework integrates a three-layer architecture: a multi-level linguistic feature extraction layer using fine-tuned transformer models, a learner modelling layer driven by longitudinal data analytics, and an adaptive feedback engine. To validate the system, a 16-week empirical study was conducted with 342 undergraduate students. Analysis of a corpus comprising 1,250 academic essays reveals that the platform significantly enhances discourse coherence (18.4% improvement) and lexical complexity (12.6% increase) compared to traditional automated writing evaluation tools. Statistical significance was confirmed via a paired-sample t-test (p < 0.01), and effect size calculations (Cohen's d = 0.76) suggest a robust impact on student writing quality. The results demonstrate that embedding evaluation directly into the system operation enables a continuous feedback loop that fosters long-term linguistic development in specialised academic contexts.

Keywords: artificial intelligence; academic writing instruction; learning analytics; intelligent educational systems; information and communication technologies; ICTs.

DOI: 10.1504/IJICT.2026.155938

International Journal of Information and Communication Technology, 2026 Vol.27 No.92, pp.25 - 59

Received: 02 Feb 2026
Accepted: 05 Jun 2026
Published online: 26 Aug 2026 *

Title: Artificial intelligence-enhanced Chinese academic writing instruction for cross-cultural communication: a framework for Sino-French and Sino-African contexts

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