Improving Education with Econometrics

Teaching and Lifelong Learning

Dr. Li Feng

State and federal policymakers frequently implement new systems intended to improve educational outcomes, particularly in low-performing schools, but these interventions are often experimental, rather than being supported by sound research on their efficacy. Dr. Li Feng, associate professor of economics at Texas State University, uses econometrics to evaluate education policy and establish causal relationships between policy and outcomes.

In one recent publication, Feng presented the first causal evidence on the effect of school accountability systems on teacher retention, helping to resolve a major debate in education policy. Her research found that in Florida, a change to the school accountability system, which downgraded many schools from a D-ranking to an F-ranking, resulted in teachers being more likely to leave schools with a stigmatized F-ranking. In another project, Feng partnered with Dr. Lora Cohen-Vogel of the University of North Carolina to evaluate the impact of teachers’ collective bargaining agreements, which give the most senior teachers preferential treatment regarding their choice of schools. Feng’s research sought to reconcile conflicting research findings from a group of researchers from Stanford and another group of researchers from UC Berkeley, but ultimately disputed the premise of a substantial correlation between preferential school-assignment for experienced teachers and negative outcomes for students. 

Feng is active in interdisciplinary projects at Texas State University, such as the LBJ Institute for STEM Education and Research, a collaboration that strives to improve access to STEM education for diverse communities of educators and students. Feng’s current National Science Foundation-funded research involves studying teachers at Texas STEM Academies, where “on average these T-STEM teachers have fewer years of experience, but a larger share of them are certified in math and science.” Contrary to the common understanding that more experienced teachers are more effective, Feng’s preliminary results suggest that these younger teachers with specific certifications are just as effective as their more experienced counterparts.

We need hands-on empirical data work in the classroom. If I invest the time and energy to train undergraduate or graduate research assistants, those students get a huge benefit from working with a professor and gaining marketable skills.

Feng is passionate about being an educator, not just researching educators. She appreciates that her research allows her to work with both undergraduate and graduate students. Feng says, “We need hands-on empirical data work in the classroom. If I invest the time and energy to train undergraduate or graduate research assistants, those students get a huge benefit from working with a professor and gaining marketable skills.” Feng’s former students have applied the skill sets she teaches — logical and analytic thinking skills, writing skills, and working with empirical data, for example — to their subsequent work with insurance companies (USAA), research firms (Buxton), technology firms (Google), and other major companies (Whole Foods).

According to Feng, contact from these former students is “the best part of my job. Yes, I’m doing research, I’m getting publications, I’m getting recognized by my academic friends and colleagues, but when I made a difference in my students’ lives I feel really great.”

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