Jeng-Shin Wu is an Associate Researcher at the Research Center for Curriculum and Instruction, National Academy for Educational Research (NAER). His research interests include educational measurement, mathematics education, competency-based assessment, teacher professional development, and the application of generative AI in educational assessment.

After graduating from the Department of Mathematics, Dr. Wu began his career in educational measurement and large-scale educational surveys. He participated in the Programme for International Student Assessment (PISA) and contributed to the development of various assessment instruments and high-stakes testing programs, accumulating extensive experience in assessment design, measurement analysis, and educational evaluation.

Since joining NAER, Dr. Wu has focused on mathematics literacy-oriented teaching and assessment. He has led several major research projects related to competency-based assessment development, longitudinal studies of mathematics literacy, and assessment practices in classrooms. His work aims to establish mathematics literacy assessment frameworks, develop assessment tasks, analyze student learning performance, and enhance teachers’ capacity for designing competency-based assessments. His research outcomes have been consolidated in the book *Good Problems for Competencies: A Guide to Developing Competency-Based Assessments* (2022), which presents systematic approaches and practical examples for developing competency-based assessment tasks.

In recent years, Dr. Wu has explored the use of generative AI and large language models (LLMs) in educational assessment. By integrating prompt engineering, retrieval-augmented generation (RAG), chain-of-thought reasoning, and multi-agent collaboration, he has developed AI-assisted approaches for mathematics literacy assessment and automated item generation. His related studies have been published in journals on mathematics education and teacher professional development, focusing on AI-assisted assessment design, knowledge-guided item generation, and methods for improving the quality of AI-generated assessment tasks.

Dr. Wu also investigates the integration of social and emotional learning (SEL) into mathematics learning. Through the project “Evidence-Based Mathematics Curriculum Design and Learning Assessment Based on International Comparative Studies,” he examines how students’ emotions, beliefs, and learning processes interact in mathematics education and develops learning frameworks that integrate both cognitive and affective development. Related research outcomes are expected to be published in 2027.

Dr. Wu’s research has been published in journals related to mathematics education, educational assessment, and educational technology. His current research focuses on mathematics literacy assessment, SEL in mathematics learning, and artificial intelligence applications in education, with the goal of advancing teaching quality, assessment effectiveness, and students’ core competencies through the integration of educational theory, curriculum design, and AI technologies.