AI in Education Spotlighted in New Infographic by FPF
Artificial Intelligence (AI) is revolutionising the educational landscape, automating tasks, personalising learning, and enhancing safety. In this article, we delve into the most common AI use cases in schools today, along with emerging trends that are set to shape the future of education.
### Automated Grading
AI systems can swiftly assess assignments, quizzes, and essays, providing rapid feedback to students and reducing teachers’ administrative workload. Leveraging natural language processing and machine learning, these systems evaluate student responses for accuracy, coherence, and sometimes creativity.
### Student Monitoring
AI is increasingly used to monitor student performance and well-being. For instance, the Kentucky Department of Education has implemented an Early Warning Tool that analyses student data to identify those at risk of dropping out or failing classes, assigning each student a Graduation-Related Analytic Data Score accessible to teachers. Similarly, districts in New Mexico are piloting an AI platform (Edia) that automates attendance tracking and parent notifications, streamlining administrative processes and improving response to chronic absenteeism.
### Curriculum Development and Customisation
AI supports teachers in developing and customising curriculum materials. Google’s Gemini in Classroom offers over 30 AI tools that help educators create content, brainstorm ideas, and differentiate instruction for diverse learners—all at no cost to schools using Google Workspace for Education. Microsoft’s Copilot is also used by educators to customise lessons based on student interests, such as integrating pop culture themes into math problems, making content more engaging and relevant. These tools act as “thought partners,” saving time and enabling more creative, student-centered lesson planning.
### Intelligent Tutoring Systems
AI-powered tutoring systems provide personalised, interactive learning experiences. Google’s Gemini in Classroom allows teachers to create “Gems”—custom AI experts tailored to specific topics or student needs—such as a “Quiz me” Gem to reinforce biology concepts. Autonomous AI tutors can assess a student’s knowledge in real time, adapt lessons to their pace and learning style, and offer immediate feedback, effectively enabling one-on-one tutoring at scale. Some states, like Iowa, are rolling out AI reading tutors that use voice recognition to assist students as they read aloud, starting in elementary schools.
### School Security
While not explicitly mentioned in the provided information, AI-enhanced school security is an emerging application. Typical uses include surveillance systems with facial recognition, anomaly detection in video feeds, and monitoring online activity for signs of bullying or threats. These systems aim to create safer school environments by detecting potential risks in real time.
## Emerging Trends
- **Agentic AI:** AI agents that autonomously manage lab experiments, provide immediate feedback, and suggest next steps in STEM education. - **Family and Community Engagement:** AI tools like Copilot help educators brainstorm event ideas and improve communication with families. - **Teacher-Led AI Experiences:** Platforms like NotebookLM enable teachers to create interactive study guides and audio overviews directly from classroom materials, fostering student agency and curiosity.
AI in education is rapidly evolving, with new tools and applications continually emerging to support teachers, engage students, and streamline school operations. The focus remains on enhancing learning outcomes while ensuring responsible and equitable use of technology.
The website Future of Privacy Forum (FPF) has recently released an infographic titled "Artificial Intelligence in Education: Key Concepts and Uses." FPF is particularly focused on AI & Machine Learning and Youth & Education Privacy. To access their resources on Youth & Education Privacy, visit StudentPrivacyCompass.org. To view all of FPF’s infographics, click here. Understanding the main types of AI, their interrelations, and how they use student data is crucial for educators, school leaders, and policymakers, as stated by Jim Siegl, FPF Senior Technologist for Youth & Education Privacy. Automated grading and feedback tools in schools, designed to free up teacher time for instruction and student support, should comply with student privacy laws and be reviewed by teachers to mitigate bias risks. The infographic emphasises the need for nuance when setting AI policies in schools, as understanding the use case and context is critically important. The AI in Education infographic can be downloaded.
- In AI-driven education, automated grading systems swiftly assess assignments, quizzes, and essays, offering rapid feedback to students and alleviating teachers' administrative workload.
- AI is also employed to monitor student performance and well-being, identifying those at risk of dropping out or failing classes, as seen in the Kentucky Department of Education's Early Warning Tool.
- Technology in education extends to curriculum development and customisation, with tools like Google’s Gemini in Classroom aiding teachers in creating diverse learning materials.
- Artificial Intelligence-powered tutoring systems, such as those within Gemini, provide personalised, interactive learning experiences, adapting lessons to students' pace and learning style.
- The future of education could see greater integration of agentic AI, autonomously managing lab experiments and providing immediate feedback in STEM education.
- To navigate AI policies in schools, it's essential to comply with student privacy laws, review tools for bias risks, and consider use case and context nuances, as highlighted by the Future of Privacy Forum's infographic titled "Artificial Intelligence in Education: Key Concepts and Uses."
