Generative AI Series: Topic Intro | Part 1 | Part 2
Generative AI and Teaching
Key Takeaway
At a Glance
Quick overview of the teaching strategy and what it involves.
Generative AI (GenAI) is a form of artificial intelligence through which computers generate content by pulling, synthesizing, and reorganizing data drawn from a large dataset. GenAI chatbots mimic the linguistic and content patterns they detect in human communication data. They are not inventing new ideas, nor can they assess the accuracy, contextual relevance, or appropriateness of the output they produce.
What Research Shows
Key findings from research studies about the effectiveness of this strategy.
Emergent research trends show that GenAI holds both opportunities and limitations for learning. In their study on the applicability of ChatGPT for science education, Cooper (2023) found that, while ChatGPT is able to produce strong and coherent responses to scientific questions, it is unable to provide clear evidence for its outputs. Darics and van Poppel (2023) argue that one of the limitations of GenAI is its tendency to conflate popularity with truth. While much of the popular and scholarly attention in higher education has centered on issues of academic integrity, Dobrin (2023) argues this foregrounds worrisome assumptions.
- 22% of students had used GenAI to complete coursework or exams (Welding, 2023).
- >50% of students indicated they considered GenAI a form of cheating and reported that neither their schools nor instructors had specified how to use GenAI ethically or responsibly.
Actionable Teaching Strategies
Concrete ideas and activities instructors can implement immediately in their courses.
- Have an explicit, transparent, and consistent AI policy. Talk with students about how, when, and why they can use GenAI tools in your course.
- Give students clear guidelines on how to think about human-computer interaction and ethical use of texts/outputs produced from that interaction.
- Reconsider your approach to assignments and assessment. Rather than trying to AI-proof your assignments, try to integrate assessment practices that have been proven to increase students’ intrinsic motivation and promote deeper learning.
- Use GenAI to support formal linguistic competence. GenAI performs well at language tasks that map onto rules-based and statistically-patterned features of English, such as grammar, syntax, tense, and words that often appear near to each other (collocates).
- Use GenAI to support functional linguistic competence. GenAI performs less well at language tasks that convey meaning in socially- or culturally-relevant ways. However, GenAI can be used as a learning tool that supports students’ ongoing fluency in American Academic English.
Student Voice
Comments and experiences from students about how this approach affects learning.
- “I’m really unsure about when I can use GenAI and when I am not supposed to.”
- “The professor walked us through how she uses GenAI for her work. Because we did it together in class, this allowed us to ask questions.”
Reflect on Practice
Questions to help you adapt the strategy to your own classroom context.
- How have you explicitly signaled to students when, how, and why they can/cannot use GenAI in your course?
- How might you model ethical and responsible use of GenAI for students so they can learn to use this tool with critical thinking and integrity?
- How can you approach the use of GenAI with multilingual students in a way that recognizes and values their existing language proficiency?
- How can you recognize and challenge implicit bias toward multilingual students and GenAI?