Ding Ning holds a PhD from Kangwon National University, South Korea. Her research focuses on modeling learning and behavioral mechanisms in human–AI collaborative contexts. From an interdisciplinary perspective integrating educational science and design research, she examines cognitive appraisal, motivational formation, and behavioral regulation processes in generative AI environments, aiming to explain how technology influences learning and work adaptation through multi-path models.

Methodologically, she employs mixed methods combining Structural Equation Modeling, fuzzy-set Qualitative Comparative Analysis, and grounded theory, with the goal of transforming complex learning and behavioral processes into interpretable mechanism-based models. In recent years, her research topics have included AI-assisted learning, technology adoption and resistance, cognitive load, and meaning construction. Related work has been published in journals such as Scientific Reports, Acta Psychologica, Frontiers in Psychology, and Sustainability, and she also serves as a reviewer for multiple international academic journals.