Classroom Examples and Pedagogical Strategies
Introduction
Incorporating AI literacy into higher education can feel like a daunting and time-intensive endeavor. This chapter highlights real-world examples of how educators are effectively teaching the competencies covered in this chapter in their classrooms. By showcasing diverse approaches, we aim to inspire and empower faculty to integrate AI literacy into their teaching practices, regardless of discipline or expertise.
Aligned with the philosophy of open educational resources (OER), we encourage the adaptation of existing approaches and resources to save time and effort while addressing the unique needs of individual educators and their students. By building on proven strategies, faculty can seamlessly incorporate AI literacy into their teaching without reinventing the wheel.
In addition to these examples, we provide effective pedagogical strategies that can be adapted to various educational contexts, along with curated resources for further exploration.
We also encourage you to contribute to this growing body of knowledge. If you have a classroom example to share, please submit it via the form below or contact us at teachingwithaioer@virginia.edu. Your insights and experiences can help shape the future of AI education in higher ed.
Classroom Example :Teaching Fundamental AI Concepts in First-Year Writing Programs
Example Overview: To introduce students to the fundamental concepts of AI in the context of writing, instructors can incorporate an H5P Module: Writing and Artificial Intelligence into their first-year writing courses. This interactive module, developed by Amy Minervini, Liza Long, and Joel Gladd, is designed to provide foundational knowledge about the role of AI in writing while engaging students with hands-on assessments.
Recommended Use: It can be seamlessly integrated into learning management systems such as Blackboard, Canvas, or Moodle.By using this module, first-year writing instructors can help students develop critical thinking skills about AI’s role in writing and its ethical implications, preparing them to navigate AI technologies responsibly in academic and professional contexts. For further customization or improvement suggestions, educators are encouraged to connect with the module’s editors.
Explore the Example: H5P Module: Writing and Artificial Intelligence.
Classroom Example: Socratic Teaching
Example Overview: Harvard Professor Michael Sandel’s approach to fostering AI literacy, particularly in AI ethics, emphasizes the power of public discourse and debate to engage students deeply in complex issues. Drawing from his renowned Socratic teaching style, Prof. Sandel encourages students to grapple with ethical dilemmas posed by artificial intelligence by questioning underlying assumptions and considering diverse perspectives. Through structured yet open-ended discussions, students explore the societal impacts of AI technologies, such as biases in algorithms, implications for privacy, and the moral dimensions of decision-making by AI systems. Prof. Sandel’s method cultivates critical thinking, civic responsibility, and ethical reasoning and is a good model for other educators in Higher Ed to explore.
Recommended Use: Below are some examples of Prof Sandel’s classrooms and teaching methods for you to explore and learn more.
Recent studies have also shown that Socratic AI chatbots can enhance students’ learnin, develop their critical thinking, as well as minimize plagiarism. We curated a list of papers and examples for you to explore below.
- The Public Philosopher Podcast by Michale Sandel
- Ethics in the Age of AI | Davos 2024 | World Economic Forum
- Michael Sandel: The lost art of democratic debate
Socratic AI Chatbots
- Crafting a Semi-Socratic Tutor with ChatGPT
- Socratic AI Against Disinformation: Improving Critical Thinking to Recognize Disinformation Using Socratic AI
- ChatGPT as a tool for honing teachers’ Socratic dialogue skills
- AI Oral Assessment Tool Uses Socratic Method to Test Students’ Knowledge
- There are also a couple of existing Socratic AI ChatGPT bots available in the Open AI ChatGPT library that you can test out.
Project Example: The AI Pedagogy Project
“We are at an inflection point in the development of AI tools — who will decide what capabilities are developed, by whom, and to what end?
We believe it is crucial for all educators, including those in non-technical fields, to contribute to these conversations— to surface questions about what it means to be human, to bring critical and historical perspectives to AI, and to revisit the goals of education, now, and in the future.”
Example Overview: The AI Pedagogy Project was created by the metaLAB (at) Harvard within the Berkman Klein Center for Internet & Society. The AI Pedagogy Project helps educators engage their students in conversations about the capabilities and limitations of AI informed by hands-on experimentation.
Recommended Use:
AI Guide – Focused on the essentials and written to be accessible to a newcomer, this interactive guide will give you the background you need to feel more confident with engaging in conversations about AI in your classroom. This guide is concise and provides interactive and hands-on tutorials on LLMs. Additionally, it has a resource section for further reading and exploration.
AI assignments – This project features a continuously growing collection of AI assignments created by educators. These assignments can be customized to your own pedagogical values and classroom needs. These assignments cover a wide range of disciplines and AI topics, such as AI ethics and AI literacy. Use the filters to search for assignments relevant to your own needs.
Reflect and Apply: Educator’s Toolkit
Pedagogical Strategies and Considerations
The process of teaching artificial intelligence fundamental concepts benefits significantly from multi-modal, experiential learning approaches. Drawing on research by Long & Magerko (2020) ,educators can leverage visual, interactive, and hands-on methods to make abstract AI concepts more concrete and accessible. When students engage with graphical visualizations and participate in interactive demonstrations, they develop a more intuitive understanding of complex AI systems and algorithms. This understanding becomes even more profound when students physically experiment with AI technology through embodied simulations, allowing them to observe and interact with algorithmic processes in real-time. Additionally, the effectiveness of learning AI fundamentals increases substantially when educators connect these learning experiences to students’ lived experiences and current interests.
For example, Teachable Machine serves as a powerful educational tool by enabling students to train machine learning models using their own images, sounds, and movements. This direct interaction with machine learning demystifies the technology by showing how AI systems learn from data in a tangible, observable way. Students witness firsthand how their inputs influence the model’s learning process, making abstract concepts like training data and pattern recognition immediately relevant and comprehensible.
This approach to fostering AI literacy embraces a significant pedagogical shift: moving from traditional instructor-centered (Sage on the Stage) teaching to a facilitator role to create a more collaborative learning environment. Educators do not need expert-level AI knowledge to facilitate meaningful learning experiences. Instead, by utilizing open educational resources and adopting the role of co-learner and facilitator, teachers can create an inclusive space where everyone participates in discovering and understanding AI concepts together.
Reflection Questions
- How does your current teaching approach align with the multi-modal, experiential learning methods recommended for AI literacy? What specific changes might help bridge any gaps you identify?
- When you consider the shift from ‘Sage on the Stage’ to the facilitator described in the document, what excites and what concerns you about this transition? How might these feelings influence your teaching effectiveness?
- In what ways could you connect AI concepts to your students’ lived experiences and current interests within your specific discipline? Consider both obvious and non-obvious connections that might emerge.
- How might the H5P Module approach described for first-year writing programs be adapted for your specific field? What unique opportunities and challenges would this present?”
- Reflecting on the Socratic teaching style exemplified by Prof. Sandel, how could you incorporate similar dialogue-based approaches to explore ethical dimensions of AI in your course content?”
- How could you create a collaborative learning environment where both you and your students can explore AI concepts together, especially if you’re not an AI expert yourself?”
- “How might you balance the need to teach fundamental AI concepts with maintaining focus on your course’s primary learning objectives? What integration strategies could serve both goals?
Use the Padlet Discussion Board to share your thoughts with peer educators.
Contribute: Add a Resource
