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AI for Higher Education Assessment
Fri, April 10, 3:45 to 5:15pm PDT (3:45 to 5:15pm PDT), InterContinental Los Angeles Downtown, Floor: 6th Floor, BroadwaySession Type: Paper Session
Abstract
As artificial intelligence (AI) technologies rapidly evolve, their integration into higher education assessment practices presents both transformative opportunities and critical challenges. This session explores the potential of AI-driven tools—such as natural language processing, machine learning algorithms, and automated scoring systems—to enhance the validity, reliability, and fairness of assessment in postsecondary contexts.
Sub Unit
Papers
Assessing Reliability and Divergence of Human vs. Al Writing Evaluation in Chinese EFL Expository - Ruonan Yang, The Ohio State University
GenAI or Teacher? How Literacy Shapes Feedback Perception - Lena Fischer, University of Twente; Mohammadreza Farrokhnia, University of Twente; Chandan Dasgupta, University of Twente; Omid Noroozi, Wageningen University and Research
Measuring Leadership within a Computational Psychometrics Framework: A Multi-Modal Analysis of Behavioral Traces with LLMs - Manru Wang, Peking University; Shiqian Huang, Peking University; Xiaoting Huang, Peking University
Measuring Student Orientation to AI-Generated Feedback in Tertiary Education: A Validation Study of the AI-FOS - Qishuai Zhang, The Education University of Hong Kong; Lan Yang, Education University of Hong Kong
Predicting Medical Exam Question Difficulty: Embedding, Machine Learning, and Feature Impact - Shicong Feng, Peking University; Tianpeng Zheng, Peking University; Hao Hang, National Institute for Communicable Disease Control and Prevention of Chinese Center for Disease Con; Jiayi Liu, Peking University; Zhehan Jiang, Peking University