Yan Ning, Vice-director of the 1^st College English Teaching and Research Division of School of Foreign Studies, Harbin Engineering University, Harbin, China.

Title: Approaches to Teaching and Evaluating Engineering English Writing in the Context of

The integration of Artificial Intelligence (AI) into higher education has brought forth great challenges and opportunities, ranging from teaching to assessment process, particularly in College English teaching as second language acquisition(SLA). Focused on Engineering English education, this paper delves into the utilization of AI technologies in teaching methodologies and assessment strategies. It examines how AI reshapes teaching and evaluating English writing, primarily in China.The paper first reviews current research on how AI drives writing instruction, concentrating on AI-based teaching design and the use of intelligent online platforms for evaluating, revising, and providing feedback on students’ writing. It further explores AI’s role in engineering English writing teaching, highlighting the substantial differences between engineering academic writing and general writing in terms of terminology, collocations, pragmatic conventions, and writing patterns. For English teachers without an engineering background, comprehending academic literature and analyzing professional documents poses great challenges. AI technology aids efficiently in collecting, organizing, and summarizing materials essential for teaching academic English in engineering, including material selection, writing samples, and discourse analysis.The paper emphasizes the development of interdisciplinary modules that blend technical content with language skills to bridge the gap between engineering expertise and proficient language use. Furthermore, it discusses the project-based and production-oriented approach in Engineering English teaching within the AI context. This includes project-based learning design, integrating MOOC and SPOC models with flipped classes, and employing online writing and assessment platforms to tailor instruction, catering to the individualized needs of engineering students. In conclusion, the paper advocates for an integration of AI-driven tools with innovative teaching methods to foster effective writing skills among engineering students, and proposes an approach, combining automated feedback with teacher’s intervention for a more comprehensive teaching practice and learning experience.

Summary: This paper explores AI integration in Engineering English education, focusing on teaching and assessment in China. It discusses AI’s role in teaching engineering-specific writing, and proposes interdisciplinary modules and the project-based and production-oriented approach based on AI. The paper advocates a blend of AI-driven tools and innovative teaching methods for effective writing skills in engineering education.