I have a position where I have access to a fairly enormous amount of data. We have formal data such as screening, state tests, and monitoring not to mention we also have other sources such as attendance and grades. In K-12 systems, there is no shortage of data. And most schools and systems look at the average score by grade and school and run some basic descriptive stats to get a better view of outcomes.
However, how do we know whether our curricula or interventions are providing a positive effect? If the results are positive, how strong are the results? Ask this in K-12 systems and you may get varying answers or no answer at all.
If one has the know-how and access, assessment data can be loaded into MS Excel and various functions are available to run descriptive stats and correlation between assessments with a fair amount of ease. However, begin splitting groups and coding some things and the task becomes a bit more complicated and time consuming. This is a great first step and answers many questions that could lead to more informed decision making. Research indicates what should work, we should run our own data and build our own evidence regarding what did actually work in our settings.
If you are fortunate or a grad student, SPSS is available and probably the most widely used and familiar program for statistical analysis. However, if lacking access to this program, this can be a substantial purchase. R is free but again, if you are not in grad school or have not been in the recent past, good luck learning this one in an timely manner. I gave up before starting the on-boarding process. Life’s too short.
Through the twitterverse, I’ve seen two free stats programs that might be provide some middle ground between SPSS and R. The first is JASP, and it appears to have a fairly user-friendly interface. Uploading csv’s and running basic descriptive stats was fairly simple and I’m no methodologist. JASP is provided by a group originating from the University of Amsterdam with an advisory board with members of numerous universities. The site offers links to “how to” resources and they are pretty active on Twitter.
The next program gaining some traction is Jamovi. Again, this one is free and resources are easily found on the site. My initial response to this one is that it may have some powerful features but I may be too novice to take advantage. This caught my attention on their site, they are striving to provide “free and open statistical software to bridge the gap between researcher and statistician”. Kudos to them and this is a needed bridge from my perspective.
To any out there who have access to district data, questions about the effectiveness of programs or interventions, and some desire to learn more about data analysis, I would encourage dabbling in either or both of these programs. I still have SPSS and it is difficult to pull away when what I have, works. But, it is comforting to know that if my subscription ends, my laptop dies, or my situation changes, I could continue to access quality statistical software.