The P3 Collaboratory is pleased to continue “Teaching Tuesdays,” our ongoing series on pedagogy in higher ed and on the RU-N campus. This summer's entry was written by Dr. Catherine Clepper.
Q: How did you spend your summer?
A: I generated love letters from David Bowie (see postscript), images of robots sipping daiquiris*, and thought really hard about that Olympic ad for Google Gemini.
If you’ve been reading email this summer, you may already know that it’s the Summer of AI over here in the P3 Collaboratory. This summer, our team has been doubling down on both our team/individual efforts to understand the capabilities and limits of new AI tools, as well as bringing AI-related training content to the Rutgers-Newark community.
So far, we have:
Learned from Rick Anderson and Suparna Sinha as they demystified AI for teaching and learning;
Considered how to integrate AI literacy into our teaching;
We have endeavored to think about AI practically, as in how (and if) to use AI technology in learning environments, while reckoning with the fact that there are no easy answers about AI ethics; see, for example, the ongoing coverage of AI’s ballooning energy consumption and climate impact. We have also tried to engage with emerging research on use of AI’s cognitive impacts on learning, although the jury is still out on many of higher ed’s most pressing questions, such as “Will use of AI impact knowledge retention?” or “How will AI change college-level writing goals and training?” See: The Department of Educational Technology’s report on “Artificial Intelligence and the Future of Teaching and Learning.”
By far the most rewarding aspect of engaging with AI this summer has been the conversations it has opened up with colleagues at Rutgers-Newark, especially the faculty participating in the P3’s Course (re)Design Institute (CDI). AI has been a theme throughout the CDI experience, from our attempts to craft learning objectives that lean in to the left half of Dee Fink’s influential “Taxonomy of Significant Learning” paradigm (see image below); through our discussion and development of AI-embedded or AI-resistant assignments; and finally, to debates around course-level engagement with AI. An approach to the latter that many CDI participants have embraced is co-designing a course AI policy with our students, instead of for our students. This co-creator approach has a lot of benefits in the classroom:
It opens up an honest dialogue between students and instructors about how course participants are already using AI.
It allows for engaged discussion around what AI can do well vs AI’s limitations.
It can add nuance to resulting course policies, normally leads away from an all-or-nothing approach, and creates buy-in from participants.
It allows students to explore their own questions, concerns, and curiosities about AI without feeling accused or judged.
It can offset the student performance gaps that can emerge when no AI-policy is articulated.**
Now that it is August (yikes!), it may be a good time to brush up on the latest (or newly improved) AI tools, read up on debates / best practices around AI emerging in your field or discipline, or consider how you want to talk to your students, advisees, and colleagues this fall about AI’s role in higher ed. Below are some recommendations to get you started!
Play with AI:
Research Rabbit: research tool
SlidesAI: presentation tool
Tactiq: notetaking tool
Adobe Firefly: image generation tool; free access for RU affiliates via Adobe Creative Cloud
Plug In to Disciplinary Conversations:
Check your field’s professional/scholarly societies to learn more on how AI is being used in related industries and/or training programs.
Investigate discipline-specific ethical and/or pedagogical concerns around use of AI
Keep Your Eyes Open for Learning Opportunities:
The P3's Summer of AI Resource Page contains multitudes!
Check back the P3’s F24 SMARTeaching lineup which will include multiple events on AI and Higher Ed/Teaching (full schedule coming soon!)
*Full Disclosure: The robot was made by the lovely and talented Fatim Outtara, the P3’s administrative coordinator, using Midjourney.
**Our thanks to Pauline Carpenter and Eliza Blau from SAS’s Office of Undergraduate Education in New Brunswick for presenting this approach to developing AI policy as part of their Rutgers Active Learning Symposium presentation earlier this summer. You can see the slides from their presentation here.
Postscript:
As an experiment, earlier this summer I ran the same prompt (“Write me a love letter from David Bowie”) into four (4) separate GenAIs: Perplexity, Gemini, Claude, and ChatGPT (shown below). I wanted to see, especially with a vague prompt, if detectable ‘house styles' emerged at all from different LLMs. The sample letters produced were all incredibly saccharine.
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