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The best education research informs real-world scenarios. This is one of the reasons I have long followed the work of David Stevens: he works with data to investigate and address issues directly impacting students. Others can apply his findings to their own efforts to improve equity and outcomes for students.
Stevens, a Nationally Board Certified Teacher (NBCT) with over 25 years of experience teaching science, math, and special education, is currently pursuing a Ph.D. in social research methodologies at the University of California Berkeley Graduate School of Education. I got the chance to interview Stevens about a paper he’ll be presenting at the 2021 California Educational Research Association (CERA) conference. His findings have huge potential to help students in need.
Jenny Rankin (JR): You’ve studied California’s Local Control Funding Formula (LCFF) in relation to more equitable school funding. How does the LCFF model work?
David Stevens (DS): The LCFF provides additional funding to student groups that are identified as being “high needs.” Currently, that includes students who are English learners, socioeconomically disadvantaged, homeless, or in foster care. A student in any one of those groups is considered to have high needs.
The weakness in this model is that when we look at student outcomes, we see that while many students in these groups are indeed high needs, not all of them are. Additionally, there are many students that are in none of those groups who are in fact high needs. While there is little harm done by giving extra resources to a student who may not need them, there is real harm done when we deny resources to a student who is in need. From my study using real student data, the current LCFF method for identifying high-need students is accurate about 70 percent of the time.
JR: Wow, that would mean a lot of high-need students slipping through the cracks. What are your recommendations for updating the LCFF model, and why?
DS: There are a couple of ways the LCFF could be improved. One would require little change and would still use the four groups mentioned previously. But, in this change, we would count how many times a student was identified as having high needs. This would give us a tiered model with four different levels of need corresponding to four levels of funding. The current method identifies only two levels. In the proposed model, an English learner who is also disadvantaged and in foster care would receive more funding than a student who is only an English learner.
Schools are held accountable for the performance of the students currently identified as high needs as well as for students served through special education and by ethnic-racial groups. Unfortunately, districts do not receive extra resources for students in those groups who may be high needs. If we aligned the LCFF and accountability, we could then identify and fund students along a six-tiered system.
JR: That makes a lot of sense. What would your proposed model mean for students and schools?
DS: In my paper I am presenting at the CERA in November, I found that the six-tier model increased the accuracy in identifying high-needs students by 11 percent. For California, this represents an approximately $700 million dollar improvement in linking additional resources to the students who need them the most. These changes could be implemented at no additional cost but ultimately we need greater investment in education to sufficiently support all students.
JR: That’s a major improvement. How does such a change relate to equity?
DS: Foundational to achievement gaps are differences in opportunities and resources. One of the ways we can best address this is to implement thoughtful policy that helps to level the playing field.
JR: I completely agree. Thank you for your time, and for all you do to help educators use data in ways that can best help students, the historically underserved, and society.
