Lecturers’ Challenges in Evaluating Student Essays in the Era of Generative AI: A Case Study of the Writing 3 Course at the Faculty of Foreign Languages, Dong Nai University
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The emergence of Generative Artificial Intelligence (AI) tools such as ChatGPT and Gemini has created new challenges for writing assessment in higher education. This study investigates the challenges faced by English lecturers in evaluating student essays in the Writing 3 course at the Faculty of Foreign Languages, Dong Nai University. The study focuses on three areas: assessing students’ authentic writing ability, differences between take-home and in-class writing performance, and difficulties related to AI policies and detection tools. A mixed-methods descriptive case study was conducted with ten English lecturers through a Likert-scale questionnaire and six semi-structured interviews. Quantitative data were analyzed using descriptive statistics, while qualitative data were examined through thematic analysis. The findings indicate that AI-generated writing often masks students’ actual language weaknesses, making it difficult for lecturers to assess genuine writing competence. A significant gap was observed between AI-assisted take-home assignments and supervised, handwritten in-class tests. In addition, the absence of an institutional AI policy and the limited reliability of AI detection tools increase grading difficulties and teacher stress. The study recommends increasing the weight of supervised in-class writing, incorporating oral defenses, and establishing clear AI guidelines to enhance assessment validity and academic integrity.
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