Assessing students’ global competence using artificial intelligence: experimental research - Sofiya Nikolaeva; Yana Diachkova; Anastasiia Syzenko (International Journal of Evaluation and Research in Education (IJERE), 2026)
This paper addresses the challenge of assessing global competencies in higher education, an essential skill set for students in today’s interconnected world. Despite its importance, current assessment methods struggle to accurately capture the multidimensional nature of global competence, often due to subjective grading systems, cultural biases, and limited resources. This paper proposes using artificial intelligence (AI)-driven assessment tools to streamline and enhance the evaluation of global competencies. Through a literature review and experimental study conducted at T. Shevchenko National University of Kyiv (Ukraine), we examine how AI technologies, such as natural language processing, machine learning, and sentiment analysis, can be applied to assess cultural awareness, communication skills, and critical thinking. The results suggest that AI-driven assessments are more efficient, objective, and capable of providing personalized feedback than traditional methods. This paper concludes that AI has the potential to revolutionize the assessment of global competencies, offering a more inclusive and effective approach to preparing students for global citizenship.