About the Evaluator
Dr. Zhina Shen is the Director of Research and Evaluation at Innovative Learning Center, LLC, specializing in STEM education program evaluation. She earned a Ph.D. in Learning Disabilities and Behavior Disorders and two M.S. degrees in Statistics and Learning Disabilities and Behavior Disorders from the University of Texas at Austin. Her expertise includes randomized controlled trials, quasi-experimental and correlational research, meta-analysis, secondary data analysis, and mixed-methods evaluation. She also has extensive experience designing qualitative studies, including semi-structured interviews and focus groups. Dr. Shen has led evaluation efforts for multiple NSF Advanced Technological Education (ATE) projects in areas such as space manufacturing, advanced driver-assistance systems, biotechnology, and construction technician training, as well as other nationally funded STEM education and research initiatives.
Evaluation Background
I specialize in...
- Mixed methods
- Culturally responsive evaluation
- Developmental evaluation
- Empowerment evaluation
- Most significant change
- Participatory evaluation approaches
- Utilization-focused evaluation
I have worked with projects in the areas of:
- ATE projects
- NSF projects other than ATE (e.g., IUSE, S-STEM, AISL, HSI, ADVANCE)
- Projects at two-year colleges
- STEM education projects supported by funder other than NSF
Training and Certifications
- Professional development workshops
- Webinars
- Online courses on evaluation
Outside of Work, I enjoy...
… playing tennis and hiking!
A Successful Evaluation...
…produces credible, timely evidence that partners can use to strengthen programs, support participants, and tell a clear story about what works, for whom, and why.
My Working Style...
…is collaborative, analytical, and responsive. I partner with teams to translate complex data into clear, actionable findings that support learning, improvement, and meaningful outcomes.
EvaluATE is supported by the National Science Foundation under grant number 2332143. Any opinions, findings, and conclusions or recommendations expressed on this site are those of the authors and do not necessarily reflect the views of the National Science Foundation.