How JMP can help transform education: Q&A with Matt Goodlaw of NM Public Ed Dept
Jul 18, 2017 7:46 AM
Matt Goodlaw, Director of the Educator Quality Division at the New Mexico Public Education Department, uses JMP and JMP Pro to analyze quantitative and qualitative data.
Summertime is here, so school is out for many people. But school improvement and research never stop. We are highlighting how state education departments use JMP throughout the year to improve educator preparation and effectiveness, and processes. This is one of two blog posts based on interviews with professionals in state education.
Matt Goodlaw is Director of the Educator Quality Division at the New Mexico Public Education Department (NMPED). NMPED uses JMP and JMP Pro to analyze quantitative and qualitative data. The data reflects educator effectiveness, such as classroom observations of teaching, student perceptions of their opportunities to learn, teacher attendance, student achievement on standardized tests, as well as other administrative data.
"I fundamentally believe that JMP can help transform educator quality, and education, more generally because it has the power to help non-technical stakeholders gain deeper and clearer insights through data analysis, quickly," Goodlaw says.
Fun Facts About Matt Goodlaw
Most used JMP platforms: Tabulate, Graph Builder and the Bivariate platforms
Favorite parts of JMP: pre-statistical analysis data steps: merging, transforming, reshaping, classifying, parsing, validating, etc. Additionally, the interactive nature of JMP report windows and Data Table windows
What was it like to learn JMP? Did you find the resources helpful?
Learning JMP was super-intuitive for me. I have some experience in statistical software; from the first time I used JMP, I have been impressed with how intuitive it is.
As my colleagues begin to learn and use JMP, they have mentioned that the resources found on the Learn JMP portion of the website is quite useful. As my skills continue to develop, I have found the in-person training courses to be highly effective for me. The JMP books, the Discussion Forum, and the Scripting Index are also resources that I use often – very often.
What improvements in your agency have been made from using JMP?
I built a small application that I was able to deploy internally, which enabled NMPED staff to quickly get the data needed to answer the questions they receive from school superintendents, principals, and teachers. Having access to the data and information at their fingertips gave NMPED staff confidence in their ability to work with school personnel at very detailed levels, which improves customer service and job satisfaction.
Do you use JMP to help answer legislative or ad-hoc questions from decision makers? If so, can you give an example?
We used JMP to perform a series of “what-if” analyses used by executive leadership at NMPED when developing or evolving policies around New Mexico’s measures of educator effectiveness (NMTEACH). Furthermore, I used the Fit Model platform to develop probability-based statements related to the impact of students reading at grade level in third grade.
Can you give an example of interesting problems that you have been able to address by using JMP?
NMPED is at the forefront of improving policies and processes around Educator Quality. JMP plays a pivotal role in our ability to compute and, more importantly, to explain our measures of educator effectiveness. Because of the graphical nature of JMP, we are completely prepared to explain and demonstrate complex models to non-technical stakeholders. For example, on several occasions we have given presentations of live data analyses of educator effectiveness that were designed to help non-technical stakeholders interpret estimates of fixed and random regression coefficients. I fundamentally believe that JMP can help transform educator quality, and education, more generally because it has the power to help non-technical stakeholders gain deeper and clearer insights through data analysis, quickly. Other statistical software may help you to separate the smooth from the rough, but JMP forces you to see, visually assess and evaluate the structure in the data, which is a big advantage when exploring, testing or confirming.