Essays
I’ve spent 30 years researching how education systems work—who gets access to what, and why. Most of that research lived in academic journals and federal reports. It reached researchers and policymakers, but not the parents and community members who could use it to ask better questions at their own schools.
That’s why I’ve started transforming this work into different formats. Using NotebookLM, each essay below is now available as a podcast, video, or lecture series. Because if you understand what the data shows, you can change the conversation.
Pick the format that works for you.
The Algebra Gatekeepers
Published on Education Progress
This essay examines what we have learned about gatekeeping in education and the critical role of the gate to advanced math. Who decides which students get access to algebra—and when? The answers reveal systemic patterns that shape student futures long before graduation. The videos and lecture series are generated from the article using NotebookLM.
The Framework
Why the behavior makes sense—even when it shouldn’t
Over three decades, we identified nine dimensions that explain nearly everything we encountered. For each dimension, people occupy one of several assumption states. State 1 represents data-informed practice. Higher-numbered states represent increasing distance from data-driven decision-making—often not from lack of intelligence, but from lack of exposure or training.
Once you know which state someone is in, their behavior makes sense. The laminated scroll makes sense. The Glamour Shots make sense. These weren’t failures of reasoning. They were logical outcomes of assumptions that didn’t match reality.
Understanding Reading Through Different Lenses
A Journey from Whole Language to Phonics
Reading proficiency is the cornerstone of education, yet the methods used to teach this essential skill have long been debated. This essay illuminates the experiences of individuals who learned to read using the Whole Language method, offering insights to those accustomed to phonics-based approaches. Through the case of Alex—a bright 25-year-old who misreads “pithy” as “panther”—we explore how reliance on visual cues and contextual guessing can impact reading proficiency, and what this means for teachers now expected to teach phonics.
The Paradigm Shift in Federal Education Grants
From Demographics to Data: What 30 Years of Program Evaluation Revealed
For decades, federal education grants targeted “at-risk” students—a term that was never clearly defined but almost always meant low-income or minority students. Programs received funding to serve these demographic groups with no requirement to demonstrate measurable outcomes. Students could remain in programs indefinitely because they never stopped being “at risk.”
Then No Child Left Behind changed the rules. Programs suddenly needed measurable goals. Services had to be linked to outcomes through research. Evaluators had to compare pre- and post-data. The federal government’s own Program Assessment Rating Tool (PART) found that almost half of Department of Education grants couldn’t demonstrate whether they were effective. Some were discontinued entirely.
As program evaluators, we saw what happened on the ground. When we finally obtained actual academic data for students being served, we discovered that on average only about 15 percent of students in any program actually met the criteria staff claimed to use. Programs designed to bring students to grade level were filled with students already at grade level. Staff selected students based on the bus they rode or whether their names “sounded minority”—and assumed this was equivalent to using academic data.
When we reported that students already at grade level shouldn’t need remedial services, program staff would ask if we were saying the students weren’t poor. The equation in their minds was absolute: low-income equals academically at-risk.
The worst discovery? High-achieving students placed in these programs regressed. Their grades dropped. Their test scores declined. The programs designed to help were causing damage.
The paradigm has shifted, but incompletely. Schools know they’re supposed to use data. Many still don’t know how—or still believe demographics are valid proxies for academic need.