Comparisons of Achievement of “Meeting Grade Level” by Texas Schools—Charter schools and ISD schools

 

Charters v ISDs. In this section you can run a program that displays the degree of success of over 7,500 Texas schools in achieving “Meets Grade Level” criteria for their students.  The MGL success data are for school year 2018-2019.  The principal focus of the displayed data is upon academic success relative to the proportion of economically disadvantaged students in each school.  The individual school data can be displayed for all the schools in each county or for all the schools in a district, and the results can be distinguished  between those for charter schools and for schools included in regular school districts.

 

The following figure provides one example of how the version of this software can be used to compare results between charter schools and regular public schools. The underlying data were obtained from the Texas Education Agency’s website, and are for school year 2018-2019, the last year for which test scores were available. Data for 7,671 schools are included—all grade levels, both charters and ISDs.

Two comparisons between charters and ISDs are shown in the figure below, one for high poverty schools, the other for low poverty schools.  The left-hand graph plots schools on the basis of the percentage of students achieving the “Meets Grade Level” criteria (vertical axis) for various average levels of student economic disadvantage (horizontal axis). The graph on the right is a plot of ISD schools versus percent economic disadvantage on the lower line, and similarly for charter schools on the upper line. When a number of high poverty ISD schools were highlighted in the right hand graph, the same schools were highlighted in the graph on the left, and average values of various data elements were written beneath the graphs. Then, when a group of charter schools in the same poverty range were highlighted on the upper line in the right hand graph, the same schools were also highlighted in the left hand graph, and the average values of the same variables written in the second line of date. The various data elements can be compared as between ISD schools and charter schools. In the example depicted in this illustration, sets of schools were also selected for both charters and ISDs at the extreme low levels of average economic disadvantage. The resulting data for these trials are shown in lines 3 and 4 in the data table. These results, and many more, can be generated using the software executed by clicking on Item 2: Show ISD-CH Comparisons, at the left of your screen. 

Though the previous discussion described how to compare MGL results for charter schools and ISD schools, the graph shown above itself, perhaps, raises a much more profound point:  there is a strong, inescapable negative relationship between the percentages of economically disadvantaged students and the average rate of those students meeting grade level criteria. Some observers look at the above left hand graph and see many high poverty schools that are performing as well as most low poverty schools. Such observations have been used to make the argument that many high poverty schools with high performance show what is possible, and what is possible within existing financial constraints.  If they can do it, others can also, they argued.  That, indeed, is indicative of some of the rhetoric that previously accompanied the No Child Left Behind program.  The testing regime that was part of NCLB did, indeed, make clear that many children were being left behind.  But NCLB was instituted 20 years ago, and look at the results shown in the graph above. The performance-poverty line is still steeply negative.  After NCLB the school choice movement gained momentum, resulting in rapid growth in charter school enrollment, including here in Texas.  There are 280,000 charter school students included in the 553 charter schools plotted in the above figure.  But, as you will see if you explore these data with the included software, the relationship between poverty and school performance is virtually indistinguishable as between charter schools and ISD schools.  Maybe, just maybe, the effects of poverty on students’ education cannot be effectively overcome until poverty itself is reduced. While it might be possible to alleviate the negative effects of poverty on education in part by providing excellent teachers to all students, the best programs to all, expanding social services and early education, these cannot be significantly expanded and upgraded without additional resources. To those who say that throwing money at the schools will solve nothing, one might ask why is it that affluent parents of children born into the most advantageous circumstances are willing to spend upwards of $50,000 per year for tuition at excellent K-12 schools? If money doesn’t matter, are those parents stupid?

 

The brief instructions contained in Items 3 through 6 should enable viewers to begin interacting with the graphs and data to explore these or other questions on their own.

Note that the two buttons beneath the data area—LHG and RHG—permit putting different graph layouts into each picture area. These and other options are described more fully in the Instructions and Examples that are linked to beneath the data table in the graphics page.

There is one additional feature added to the ISDCH version of this software, linked to on the left, which is not described in the Instructions, namely the ability to highlight or select all of the schools in a particular county.  The county-selection list will appear after clicking (LMB) on the white box labeled “County” near the bottom of the screen.  If the [Hlt/Sel] button is “On” (red) when this selection is made, the schools contained in the selected county will in fact be selected.  Only those schools will be plotted, and they can be further queried with mouse action by creating a rectangle around one or more points (click, move mouse, click again).   On the other hand, if the [Hlt/Sel] button is “Off” (white) when a county is selected the schools in the selected county will merely be highlighted, colored by district.

Questions and feedback are welcomed.  I can be reached at ltoenjes@aol.com .

Larry Toenjes

Clear Lake Shores, TX