Explainable AI for Enhancing Awareness of Academic Stress Among International University Students

Academic stress is a common challenge in higher education, especially for international university students who must adapt to new academic systems, expectations, and learning environments. In recent years, artificial intelligence has been increasingly used to analyze academic data and estimate student stress. However, most AI-based systems prioritize prediction accuracy over providing valuable support for student understanding. As a result, students may receive stress-related indicators without a clear explanation of how these results relate to their academic tasks or activities. This state-of-the-art review discusses current research on explainable artificial intelligence in the field of academic stress and student awareness. Based on literature published between 2020 and 2025, this review synthesizes work from educational technology, learning analytics, and explainable AI from a Human–Computer Interaction perspective. The analysis focuses on the representation of academic stress, the design of explanatory frameworks, and the extent to which existing systems facilitate students’ ability to interpret and reflect on their work. The review finds that awareness is rarely treated as an explicit outcome in existing research. Although explainable models are increasingly used, the explanations they produce are often technical and not student-oriented. International students are an underrepresented group in the literature, despite the apparent differences in their academic preparation, linguistic ability, and expectations. Consequently, these shortcomings limit the effectiveness of artificial intelligence systems as tools for enhancing student awareness. This review highlights the need to shift from prediction-oriented approaches toward awareness-oriented explainable AI systems that prioritize student understanding. By emphasizing human-centered explanation design and inclusive evaluation, future research can better support students in making sense of academic stress within diverse higher education environments.