Compare Apples To Apples With Cast Data
By Dr. Mathew d'Alessio, CSU Northridge Professor
Most of what the CAST data show are systemic issues in supporting emergent bilinguals and other historically marginalized students, and those long-term effects of systemic failures of society go beyond the school system.
On my quest to help classroom teachers get value out of CAST scores, I spent my sabbatical creating a new way to view the CAST data (http://dataninja.greenninja.org). The goal is to compare apples-to-apples.
When we look at CAST data, we often use the wrong basis for comparison and we only see the result of these systemic failures. Figure 1a shows one district's achievement gap where English learners fall below the standard more than twice as often as native English speakers. While every educator needs to take that challenge on, it's a systemic issue that goes beyond what a classroom teacher can do.
Figure 1b shows what happens when we shift the basis of comparison: how do students in this district compare to similar students statewide? This district actually serves EL students better than the average EL student statewide. When students get reclassified, however, they underperform compared with students with similar backgrounds statewide. The district can now evaluate and adjust its reclassification policies.
With this view in mind, we can spot failures that are within the locus of control of our school system and shine lights on successes that can be replicated more broadly. Here are some examples of what I've seen when working with districts to analyze their data:
CAST data comparison |
Suggested Action |
|---|---|
| Girls at one school vastly outperform boys, and the pattern is consistent from year-to-year but isolated to this school within the district | It turns out that the all-female science faculty at this school encouraged counselors to place girls in more science. Maybe similar conversations should take place district-wide. |
| Homeless students at one school vastly outperform homeless students statewide | It turns out that this school has impressive wrap-around services. Consider deploying them more broadly. |
| A school's economically disadvantaged Hispanic students vastly outperform the district-wide average for that subgroup. | If the pattern is consistent across ELA and math, look at the school culture for replicable systems. If it's just science, look at the instructional practices and use them as a model district-wide. |
| In a district doing better than average overall, students from families whose parents never went to college are doing poorer than the county-wide average for that group. | The district should consider targeted outreach to this group of students and/or parents to figure out what they are missing and how to fill in the gaps. |
So try out the Data Ninja to compare apples to apples for your district. What actionable items can you spot?
About the Author
Dr. d’Alessio sees science from the perspective of both a researcher and an educator. He was a research scientist at the U.S. Geological Survey, is currently a Professor at CSUN where he teaches science to university students and future teachers, was a high school Earth Science teacher in an urban public school, ran a sustainability education program in local elementary schools, and spent a year as a stay-at-home dad. He drew upon this complete picture of science from 'top to bottom' as one of the lead writers of the 2016 Science Framework for California Public Schools. In 2018, he received CSUN's university-wide Distinguished Teaching award.
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