Written by
Sarah Singer
•Senior Director, Education Solutions
AI will transform analytics in K-12 education. While this blog provides a few examples, note that I’m only scratching the surface. Greater use of AI-powered tools will create teaching and learning opportunities the education ecosystem has aspired to but not yet realized.
How AI Will Build Data-Driven Cultures
Let’s start with controversy. Data-driven decision-making has become an over-used term. I think it’s analogous to when the doctor says, “Eating your vegetables is important.” Of course it’s important. We know this! But what if there was some magical thing that would suddenly make us eat vegetables with the same mindless fervor that I eat popcorn while watching a movie?
I believe AI could be this magical thing when it comes to building a data-driven culture.
Different skill sets will be prioritized when this new culture forms. The ability to ask the right questions and conduct root cause analysis to understand how to best support a student, teacher, or school will be rewarded. Other skills will be de-prioritized, such as the ability to navigate a user interface on a software program or the ability to manipulate spreadsheets in fancy ways.
To share my perspective, I’d like to review the journey of analytics in K-12 over the past two decades.
First Phase: Data Wizards Rule the Day While the Rest of Us Look From Afar!
Sometime in the early to mid-2000s, analysis was all about spreadsheets. Researchers prepared spreadsheets of assessment data for teams to review. Of course, none of this data was drillable to the student level. Some of this data was even printed on paper and placed in binders!
Meanwhile, “data wizards” might impress their colleagues with fancy spreadsheet machinations such as pivot tables, v-lookups, and the occasional macro. These individuals were the go-to people in the organization on all things data. This meant they had disproportionate power in setting the data culture, leaving out others who had deep knowledge of student needs, but perhaps not top-notch spreadsheet skills.
Second Phase: Analytics Platforms Bring Data Access and Insights!
Eventually, technology came to the rescue. Analytics platforms, such as PowerSchool’s Student Analytics, were brought to the forefront. This included the ability to house a one-stop shop for all data, including assessment, attendance, behavior, social and emotional learning (SEL), enrollment, talent analytics, and more. With this platform, end users can view data in aggregate and then with one click drill to the student level. This data is transformative for education organizations. Researchers and data analysists are still needed, but their expertise can be diverted to other critical tasks rather than spending hours connecting disparate source systems for the purposes of creating spreadsheets.
The Next Frontier: AI Democratizes Data, Driving Decision-Making
Even when data access and insights are technically there, K-12 organizations still sometimes struggle to build a data-driven culture. Data culture can often live solely within Professional Learning Communities (PLCs) or grade level meetings, when groups of educators, with laptops out, collectively review student data.
But AI has the potential to transform the use of data by making data-driven decision-making more ubiquitous due to its ease of use. AI systems enable new forms of interaction, such as the ability to “talk to your data.”
Rather than navigating a platform, clicking several times, and then viewing data on a dashboard, an end user may instead talk to a computer, tablet, or mobile device. “Tell me which of my incoming fourth graders were not proficient on the state assessment in ELA (English Language Arts).” Then the application displays a visual of the information.
That data can be broken down even further. How many of these students received interventions last year? What were the interventions? Of these students, how many were chronically absent last year? This information is quickly gathered and requires no navigation of a platform. It simply requires sound inquiry and diagnostic skills. AI can then produce high-level insights from the data generated in the form of a narrative. All of this can happen during that formal PLC meeting, but it can also happen quickly in impromptu settings.
The technology will allow educators, including those who perhaps previously didn’t have strong technological proclivities, to access information in a new way. A byproduct is that this will provide them with a greater voice within a district’s data-driven culture. It will also provide insights in the moment to enable educators to better meet the on-demand needs of students as they emerge.
That’s what will make AI different. Data use will become more ubiquitous because it will become so easy to manage and consume.
PowerSchool is on the precipice of making this a reality. In the future, this functionality can be embedded into existing education technology systems, such as PowerSchool Analytics, an LMS like Schoology Learning, a SIS (PowerSchool SIS), or an assessment platform (Performance Matters). At PowerSchool, this means we are bringing AI to your data, not making you push data to untested, niche AI providers. This will help to ensure the responsible use of AI.
Responsible AI
This brings me to the last set of critical points. AI solutions have an increasing impact on education with a potentially transformative effect. As we build novel applications that use artificial intelligence, we must be committed to solely focusing on solutions that positively impact education. To maintain a mindful and responsible approach to AI, organizations should be guided by foundational principles to ensure its proper and ethical use.
For example, one critical principle is that AI should be human-centered. The recent report by the U.S. Department of Education Office of Educational Technology, titled “Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations,” states it nicely when it recommends that we “pursue a vision of AI where humans are in the loop. That means that people are part of the process of noticing patterns in an educational system and assigning meaning to those patterns.”
PowerSchool has developed a set of its own guiding principles on AI use, which can be found in the blog The Ethics of AI in Edtech: Ensuring Student Success in a Digital Age. Before adopting any edtech solution, every educational community should ensure it thoroughly understands how the provider will use AI. Is your data being managed in a secure and ethical manner? Are you required to surrender your data to AI instead of bringing AI to your data? Modern, responsible, and ethical AI use can help all of us be more creative, empathic, and innovative. It will also help districts build an effective data-driven culture once and for all.
About Sarah Singer
Sarah Singer brings more than 10 years of education experience to her role at PowerSchool. She now helps K-12 education agencies create strategic plans for building a data-driven environment.
Sarah entered Portland Public Schools in 2007 as a Broad Resident in Urban Education, a national and highly selective two-year management development program that recruits and trains emerging leaders for senior management positions in public education. She went on to serve as the Senior Advisor to the Chief Academic Officer. Later, she oversaw the Research, Evaluation, Assessment, Administration, and Analytics Departments in the district.