AI Literacy: A Must-Have Skill for Future Success
- PAST Foundation
- 1 day ago
- 4 min read
By Jeff Schneider, PAST Foundation Teaching & Learning Innovator | <4 min read.
Introduction
By combining transdisciplinary, problem-based learning (PBL) with the Design Cycle, educators can foster creativity, ethical awareness, and deep learning while addressing real-world challenges. This approach equips students to navigate an increasingly AI-driven world while developing essential skills for future success.
Top 6 Resources for AI Literacy in Classrooms
1. MIT RAISE AI Literacy Units
Link: MIT RAISE Resources
Description: Offers interdisciplinary projects like designing AI-powered apps to address community issues (e.g., environmental monitoring, health equity).
Implementation Insight: Use these units to guide students through brainstorming, research, and design phases of the Design Cycle to create solutions for local challenges.
2. Digital Promise: AI Literacy Framework
Description: Focuses on understanding and critically evaluating AI systems through real-world scenarios like auditing hiring algorithms for bias.
Implementation Insight: Assign students to analyze an AI tool's fairness during the evaluation phase and propose redesigns during the modification phase.
3. ISTE’s Hands-On AI Projects for the Classroom
Link: ISTE Guide
Description: Features project-based modules such as designing chatbots or exploring the societal impact of autonomous vehicles.
Implementation Insight: Pair science and social studies classes to design AI solutions for infrastructure challenges during the build phase.
4. Eduaide.ai: Project-Based Learning Suite
Link: Eduaide.ai
Description: Generates wicked problems (e.g., “How might AI reduce plastic pollution?”) with scaffolding for research, prototyping, and pitching solutions.
Implementation Insight: Use this tool during the brainstorming and research phases to create collaborative design challenges that connect math, science, and social studies.
5. Code.org: AI for Oceans
Link: AI for Oceans
Description: An interdisciplinary activity where students train an AI model to clean ocean plastic while learning about machine learning principles.Implementation Insight: Combine this activity with lessons on environmental science during the build phase to explore broader implications of AI in sustainability.
6. Create & Learn: Fun Artificial Intelligence Activities
Link: Create & Learn BlogDescription: Features creative projects like building chatbots in Scratch or experimenting with face-sensing technology through Scratch Lab.Implementation Insight: Have students create chatbots during the design phase that answer questions about a specific topic (e.g., climate change), integrating STEM with communication skills.
Implementation Insights
Start Small with Existing Tools: Begin with accessible platforms like Code.org or Eduaide.ai that require minimal setup but offer high engagement. Integrate Across Disciplines: Use PBL to create projects that combine STEM with humanities (e.g., ethical debates on AI’s role in society). Foster Ethical Awareness: Incorporate discussions about bias, privacy, and misinformation into every project to build conscientious use of AI tools.
Encourage Collaboration: Assign group tasks that require students to use AI tools collaboratively while addressing real-world problems (e.g., designing smart cities).
Leverage the Design Cycle: Follow its phases systematically to ensure deep thinking and iterative refinement of student projects.
Description: This document outlines a structured framework for implementing PBL through iterative phases: Brainstorm, Research, Design, Build, Evaluate, Modify, and Share. It emphasizes critical thinking, collaboration, and reflection at each stage.
Implementation Insight: Use this framework as a guide for creating transdisciplinary design challenges that integrate STEM concepts with humanities and social sciences.
Expand Your Approach with Hacking School: Five Strategies to Link Learning to Life. Dr. Annalies Corbin’s book provides five transformative strategies—Student Agency, Culturally Relevant Education, Mastery Learning, Transdisciplinary Teaching, and Problem-Based Learning—that empower educators to create meaningful learning experiences. These frameworks align directly with fostering AI literacy and implementing design challenges.
Conclusion
AI isn’t some “future” thing—it’s already here, shaping how we work, live, and even how students learn. In fact, 54% of students globally are already using AI in their studies, and over half use it weekly, according to the Digital Education Council.
Teaching AI literacy isn’t just about understanding the tech—it’s about giving students the skills to thrive in a world driven by innovation and creativity. And with Brisk, it’s not only simple but dare we say, actually fun.
By leveraging curated resources, the Design Cycle framework, and insights from Dr. Corbin’s Hacking School, educators can create engaging learning experiences that prepare students for the challenges of an AI-driven future.
AI isn’t some “future” thing—it’s already here, shaping how we work, live, and even how students learn. In fact, 54% of students globally are already using AI in their studies, and over half use it weekly, according to the Digital Education Council.
Teaching AI literacy isn’t just about understanding the tech—it’s about giving students the skills to thrive in a world driven by innovation and creativity. (Brisk Teaching, 2024, para. 2)
Reflection Prompt: How might you adapt one of these activities or phases of the Design Cycle to suit your classroom’s unique needs?
Share your questions or ideas with the PAST Foundation at jschneider@PASTfoundation.org
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