Looking for AI Tools for Education with Sample Classroom Uses?
You can find a few listed in this Gamma presentation deck.
Over the last few days, I’ve been playing around with the PRISM Framework, a framework that scaffolds thinking. It is inspired by the SOLO Taxonomy. The PRISM Framework is intended to support thinking as it moves from unistructural to multistructural to relational to extended abstract, as defined in the SOLO Taxonomy. Simply, this means shifting from having no idea to some idea to several ideas (but not knowing how they connect) to seeing how ideas and perspectives connect but unable to make sense of the pattern. It concludes with coming up with a hypothesis of how things fit together and ways to test it.
PRISM takes each of those an generates questions and ideas. I have a few blog entries planned that explore PRISM planned for publication elsewhere, but I’m starting to use PRISM for other things, as way to get thinking going around AI in education, and other topics. Since PRISM is a scaffold for thinking, you can really use it for anything. What’s even more fun, I’ve created a Perplexity Space to assist with applying PRISM to new ideas.
Here’s an AI-generated PRISM relevant to AI in education. It includes updates statistics. Citations have been removed.
A PRISM Analysis: AI in K-12 Education
Patterns
AI adoption in K-12 spread unevenly in 2024. Automated tasks, personalized learning, and cloud management led. Advanced applications lagged. 30% of schools deployed AI, up from 25% in 2023. 80% of teachers use AI-powered platforms weekly.
“I’ve noticed AI creeping into our classrooms, mostly for grading and attendance. It’s like having an invisible teaching assistant.”
Reasoning
Schools adopted AI for efficiency and personalization. It cut teacher workload and boosted engagement. Challenges slowed progress. Infrastructure gaps, lack of training, and privacy concerns held back integration. Only 18% of teachers used AI for teaching in 2023. 37% of districts planned training by 2024.
“AI connects to our need for efficiency, but it’s a double-edged sword. It helps with grading, but we’re still figuring out how to use it safely and effectively.”
Ideas
To improve: Blend AI analytics with teacher interventions. Build comprehensive AI ecosystems. Fix infrastructure. Train teachers. Suburban schools lead in AI training at 23%. Urban and rural schools trail at 17% and 16%. Two-thirds of teachers plan to use more AI soon.
“What if we combined AI-driven analytics with our expertise? We could create personalized learning experiences that truly meet each student where they are.”
Situation
AI reshapes more than classrooms. It impacts district policies, teacher development, and home-school links. It aligns with hybrid learning and future-ready education. 52% believe schools should teach AI use. Only 19% of teachers used AI in their training.
“The bigger picture shows AI isn’t just about classroom tech. It’s changing how we approach education as a whole, from policy to parent communication.”
Methods
To test AI’s impact: Compare outcomes in AI-enhanced and traditional classrooms. Track adoption across demographics. Audit data privacy. Newer teachers use AI more: 21% for those under 10 years, 17% for veterans. High school teachers view AI more negatively than elementary teachers.
“We can validate AI’s effectiveness by comparing student outcomes, but we must also ensure it’s equitable and protects student privacy. It’s a balancing act.”
