Cody Ding, Ph.D.

Dr. Cody Ding completed his Ph.D. at the University of Minnesota, Minneapolis. He was trained as a psychologist with an emphasis on developmental psychology, methodology, and measurement. Over the years, he has been working as a professor at universities, teaching educational and psychological assessment, research designs, behavioral analysis, statistical modeling, and other methodological related courses. Currently, Dr. Ding is the director of the educational psychology and educational research program. In addition, he has been working with many school districts and state educational agencies on various evaluation projects to improve student learning and school practices.

With expertise in quantitative methods and research design, particularly growth modeling and classification and predictive modeling, Dr. Ding focuses on multidimensional scaling, data visualization, and multilevel modeling. Psychometric expertise includes item response theory and multidimensional scaling applied to measurement and evaluation research. Dr. Ding has been actively involved in research on multidimensional scaling as a latent growth model in education and psychological assessment. His research interests include exploratory latent variable analysis via multidimensional scaling (MDS), applications of Item Response Theory (IRT), machine learning, network modeling, and Structural Equation Modeling (SEM) in studying the psychosocial adaptation of adolescents and young adults, such as emotional and social skill development. Relatedly, Dr. Ding is also a faculty in the school psychology program, applying his expertise in mental health, learning, and behavior to help children and youth succeed academically, socially, behaviorally, and emotionally. Operating from a problem-solving framework, his focus is on preparing data-based decision-makers capable of intervening to address both individual- and systems-level challenges in the school setting. 

Dr. Cody Ding has been conducting substantive research regarding the effects of social experiences, particularly negative ones, on cognition/attention, which may lead to psychological distress. The research also includes dynamic interaction between teaching and learning. The research is based on data from questionnaires, behavioral experiments, and neuroscience studies. He has provided high-level consulting services to quantitative researchers in the social and behavioral sciences, including several evaluation grants investigating the program's effectiveness on student learning.

Program Involvement

• EdS - School Psychology
• Grad Cert - Program Evaluation Certificate
• PhD - Educational Psychology

Published Research Areas

1) Quantitative Methods, Measurement, and Psychometrics

Scope: Multidimensional scaling (MDS), growth/mixture/hierarchical/structural models, test theory, visual analytics, Bayesian networks, and applied machine learning for education.

 

2) Learning, Cognition, and Educational Outcomes

Scope: Literacy and math learning, cognitive processes in learning (attention, memory, executive control), school/teacher effects, and assessment systems.

 

3) Emotion, Mental Health, and Self-Regulation

Scope: Emotional intelligence (EI), mindfulness, depression/anxiety, adversity and stress, well-being, character/virtue, and smartphone/Internet problems.

 

4) Social Context, Adolescence, and Risk/Health Behaviors

Scope: Adolescent development, rejection sensitivity, aggression, loneliness/social exclusion, trauma/earthquakes, cultural identity, at-risk youth, and athlete performance/burnout, team/organizational EI, decision-making styles, sleep/aging, social connectedness, and health/education interfaces.

 

5) Neurocognitive and Affective Neuroscience

Scope: ERP/fMRI studies of inhibition, reward/attention, emotional modulation, OFC-amygdala connectivity, working memory, interoception, and social perception.