Spotlight on K-12 Data Analytics

Data, Data Analytics, Data Science—these fields are helping shape almost every industry and institution, and K-12 education is no exception. Using data points can help boost student performance and predict pathways for successful future learning outcomes. James Fleming, executive director of Professional Services at Illuminate Education, has experience using data analytics in the K-12 environment, and sat down with School Planning and Management to answer a few questions.

Q. What are some new or different ways in which data is helping students get the most out of their education? Are there new ways of examining data over time to maximize achievement?

A. One of the next frontiers in education is social-emotional learning (SEL). After a period of laser-focus on high-stakes testing, the nation’s policy-makers are remembering how important it is to educate the whole child, which includes social skills, emotional skills, and wellness.

Illuminate has been working with the CORE districts for several years to simplify the collection of SEL data. Students take periodic surveys to describe their growth mindset, self-efficacy, self-management, and social awareness. The CORE districts know that when aggregated together, these four dimensions help the participating schools describe their student’s growth as well-rounded global citizens.

Teachers are waking up to the importance of social skills as well as academic skills. Going forward, Illuminate anticipates that educators are going to be looking at social-emotional health as a contributing factor to academic growth. We’ll see the biggest academic gains from schools that have learned to use SEL education to unlock their student’s potential. Use of SEL data will make schools more responsive to student needs and a happier place to be.

Q. Are there any drawbacks to using analytics and student data to track progress? If so, how can these be countered?

A. There are huge ethical implications around how educators use data. Our own Chief Data Scientist Chris Walker led a packed session on this exact topic at SXSW in 2018. While the rest of the EdTech presenters were ready to rush full-speed into the use of machine learning and artificial intelligence, Chris was one of the few voices advocating for caution—it's important to remember that education data sets can have embedded bias.

Analytics and predictive models are only as good as the data that drives them. It borders on educational malpractice to take a hands-off approach when data sets are making decisions about students. Certainly, A.I. and machine learning open up new horizons for education, but we know that a human needs to stay engaged and in control of the decisions. Passionate and informed educators are our best chance of closing achievement gaps and improving educational outcomes for all students. We firmly believe that an informed educator is better for a student than any algorithm.

Q. How will the use of student data change in the future? Will it continue to inform the way administrators and teachers work with students? 

A. Education is awash in data, and the reality is that the amount of data is only increasing. Educators don’t need more data—they need better ways of turning data into insights. Helping teachers and administrators understand a student’s trend line can inform what the student needs next.

Take two students who are both reading below grade level. The first student is reading below grade level, but is making moderate, steady gains. If the student remains on track, she’ll be caught up by the end of the year. The second student may be testing higher than the first, but if he’s not showing growth, he's going to be further behind by the end of the year. The data is the current reading level, but the insight comes from inspecting the trend line over time.