General Considerations for the Classroom
Generative AI and Large Language Models (LLMs) provoke many questions and dilemmas around education and pedagogy. Whether you choose to use LLMs in your course or not, Generative AI tools are a part of today’s educational, cultural, and workplace landscapes. How will you respond to this new landscape?
One way to respond to AI in education is the “Robot-Proof” model, coined by president of Northeastern University, Joseph Aoun. In Aoun’s book, Robot-Proof, proposes a way to educate the next generation of college students to invent, to create, and to discover—to fill needs in society that even the most sophisticated artificial intelligence agent cannot (Aoun, 2017). Robot proofing is not anti-technology but rather responds to evolving technological landscapes and encourages intentional application of technology.
Beyond highlighting the importance of preparing students for AI in the job market, “robot proofing”, can be a helpful concept in shaping your teaching and learning. How can we “robot proof” our courses, learning goals, and assessment, such that our students are asked to engage and demonstrate learning in ways that robots, like LLMs, cannot?
Many student-centred best practices in teaching and learning make great “tools” in “robot proofing” education. Application of pedagogies and strategies that engage critical thinking, problem solving, self-reflection, local-global impact, and experience prompt students in learning and innovation that is student-centred and not easily replicated by LLMs and AI broadly.
- Transform course syllabi, Learning Goals, Objectives, and Outcomes to promote innovation and curiosity such as Inquiry Based Learning or Active Learning
- Create lessons that involve identifying and responding to real world problems through Problem Based Learning and Case Based Learning models which prepare student’s to make an impact in their community and career
- Support student development by making self-reflection and understanding of perspective and Positionality key components to learning and assessment: Positionality Statement
- Facilitate Experiential Learning Opportunities like Field Based Learning that involve practice and application to engage, review, conclude, and plan.
- Develop a Globally Engaged Curriculum that reflects global and intercultural perspectives to encourage not only student work-competencies across cultural contexts but to demonstrate social responsibility.
- Encourage critical thinking, self-reflection, community-oriented learning by imbedding Indigenization-Equity, Diversity, Inclusion, Anti-racism, and Accessibility (I-EDIAA) principals in the foundation of your course content, process, and culture.
- Uphold commitments to Decolonizing and Indigenizing education through holistic and learner-centred centred pedagogies such as Pedagogy of Peace to foster greater cultural safety, self-reflection, and accountability in your classroom community.
- Apply accessible-best practices in the classroom, such as Universal Design for Learning (UDL), which encourage diverse and student-centred means of engaging and demonstrating learning.
- Use Educational Technologies that enhance student engagement in critical thinking. If you choose, use LLMs thoughtfully to promote learning process, problem solving, inquiry, and self-reflection.
- Implement Authentic Assessment practices to ensure course deliverables advance knowledge of “how” rather than “what” and demonstrate student’s holistic learning process.
As you learn more about LLMs and make intentional “next steps” for your course design, assessments, and syllabi, consider how you can use best practices in teaching and learning to work with, alongside, or challenge the use of AI in education.
Resources
How chatGPT answers prompts ChatGPT Experiments with Sample Assignments (1).docx
ChatGPT use in American classrooms ChatGPT In the Classroom - Alex (WORD, 32KB)
Talk to your Students
This resource was adapted and remixed from the Maloy, R. W., Trust, T., Butler, A., & Xu, C. (2021). Critical Media Literacy and Civic Learning. EdTech Books. and adapted to Queen’s University context. All content is licensed under CC-BY-SA.
Start by talking to your students. Using critical media literacy, the following guide offers foundational questions you can prompt your students with regarding Generative AI. The questions focus both on the forward-facing content as well as behind-the-scenes work for the medium. The questions address both representation of the power of construction and of distribution. The questions are intentionally broad - they will best be used to begin the process of analysis.
Questions About the AI Writing Tool
- Who created the AI writing tool?
- Who worked on training the AI writing tool?
- What dataset was used to train the AI writing tool? How does the diversity (or lack thereof) of the dataset influence the output of the AI writing tool?
- What do the privacy policies say?
- What are the limitations of this tool? (e.g., ChatGPT is not connected to the Internet, and therefore, cannot generally (though not always) draw connections to present-day events ; ChatGPT has a limit for how much text you can upload)
- Who is harmed and who benefits from this tool?
- What are the unintended and unexpected benefits and consequences of using this tool?
Questions About the Text Produced by the AI Writing Tool
- What information is presented in the text?
- What information is missing from the text? Why do you think that information is missing? (consider that ChatGPT generates text based on its training dataset)
- What type of language and word choices are used to convey ideas and information in the text?
- How are the language and word choices different from, or similar to, the way humans write? Why do you think that is?
- Who is the target audience(s) for this text? How do you know this?
- How reliable, accurate, and credible is the text? How did you determine this?
- What sources , if any, are cited? How accurate and relevant are those sources?
- What biases are present in the text? Why might this be?
- What might be the original sources used to generate this text? Conduct an Internet search and see if you can find the original source (it's likely more than one source!) that the AI tool used to generate this text.
Student Academic Success Services (SASS) at Queen's has created a host of online guides and tutorials on academic integrity, strategies to improve note-taking, managing writing, as well as the following module on generative AI, which walks students through responsible GenAI use. As an instructor, you can embed the module directly in your OnQ:
For more information please email SASS or telephone us at 613-533-6315.
This Creative Commons license lets others remix, tweak, and build upon our work non-commercially, as long as they credit us and indicate if changes were made. Use this citation format: Generative AI in Teaching and Learning. Centre for Teaching and Learning, Queen’s University