Top 5 uses for AI in K-12 Education

The potential impact of artificial intelligence (AI) on K12 Education is being heralded as both extensive and multifaceted. Proponents point to AI spurring adoption of personalized learning, intelligent tutoring, automated grading, and streamlining data analysis while improving teaching practices.

Personalized learning

“We’re now able to capture moment-to-moment data,” says Dan Schwartz, dean of Stanford Graduate School of Education. He explains that data can then reveal areas of struggle and learning opportunities for individual students. For example, the learning opportunities could help individual students to solve math problems or how to approach a writing assignment. The promise of personalized learning is being able to generate content aligned with students’ interests and skill levels, and making lessons more accessible for all students, including multilingual learners and students with disabilities.

Intelligent tutoring

Intelligent tutoring systems (ITS) can deliver immediate feedback, while boosting engagement, retention, and overall learning outcomes.  By collecting and analyzing performance data, ITS helps find patterns and trends, fueling decision-making in curriculum and instruction. There are edtech tools available today that are adaptive AI tutors that personalize math instruction for middle and high school students and beginning in 2024 these tools branched out into solutions for literacy, languages, tutoring and even professional learning for teachers and leaders. This data-driven approach allows for continuous improvement and adaptation to meet the evolving needs of students. With an ITS, personalized learning can be delivered to a large number of students efficiently.

Automated grading

AI can grade multiple-choice questions, fill-in-the-blank answers, and supporters claim it can even grade some forms of essay writing with a high degree of consistency. These systems can grade the results of thousands of students efficiently and provide instant feedback. Adoption of such systems can greatly reduce the amount of time teachers spend on mundane tasks, freeing them to concentrate on teaching and curriculum.  

Data analysis

Schools and districts can use AI to look at student attendance data, historical test data and instructional strategies, and then pull all of that data together to make predictive analyses.  For example, a district could use an agentic AI system to create a strategy to increase attendance. Moreover, data analytics can inform curriculum development and instructional strategies, leading to improved educational practices and results.

Optimizing teaching practices

Teaching requires significant planning time to account for the various needs of students in their classrooms — particularly for inclusive learning environments and students with IEPs and 504 plans. AI can help teachers with recommendations based on prompts that describe their situation. AI can also help in adapting found materials to fit their exact classroom needs.

For students with an Individualized Education Program (IEP), AI can help find components to add to lesson plans to meet an individual student’s requirements. Further, AI can help adapt standardized resources to better fit specific needs —for example, providing a voice assistant that allows a vision-impaired student to hear material, or permitting a student to present their project using American Sign Language (ASL) which could then be voiced for the whole classroom using an ASL-to-Spoken-English AI capability. 

Overall, teaching is time-consuming work that might receive help from the automation and customizable interactivity provided by an AI. Teachers almost always want to do more with each student than they can, given the limited number of hours available. A teacher may want to guide a student as they practice 10 math problems, offering them ongoing support. But if that teacher can only carve out the time to sit with a student for two problems, perhaps they could delegate to an AI-enabled learning system to help with the rest.

AI needs reliable connectivity to succeed

To deliver on the promise of AI, schools need fast and reliable access to the internet, cloud services, and applications with a secure dedicated internet connection backed by a 100% uptime service level agreement guarantee, end-to-end.

Connectivity needs for AI usage focus on high bandwidth, low latency, reliable connections, and robust network infrastructure to manage the data generated and processed. Essentially, a network that can seamlessly support the constant flow of data needed for training and employing AI models. 

Fiber networks are well-suited for AI applications due to their high bandwidth and low latency capabilities. These networks can support the massive data transfer required by AI, and the best fiber networks offer resiliency and a higher resistance to interference. This is crucial for AI applications which require constant, reliable uptime to deliver optimal results.

Spectrum Business can help

One-size-fits-all technology solutions just don’t work. That’s why we customize our technology solutions to each K-12 institution’s unique needs. Whether you’re a public, charter, religious, or private school, we’ll help you create a technology-rich learning environment that helps students succeed.

For more than 20 years, Spectrum Business has partnered with K-12 schools, districts and libraries to provide managed education services tailored to evolving needs. With our wide range of managed services and networking technologies, we can help you extend your funding and create education solutions that support new levels of student achievement.

Find out why the two largest K-12 school districts in the U.S. rely on Spectrum Business for technology solutions.

Going to ISTE?

We’re excited to meet with K-12 innovators at ISTELive 25, June 29–July 2, in San Antonio, Texas. Join Spectrum Business, a top E-Rate provider, at Booth #1860 and we can discuss how our education-specific solutions power secure, reliable connectivity for students, educators and staff.