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Robert Cole

@robertsplace.bsky.social

Instructional developer interested in generative AI, how we assess and grade students, and curriculum and course design. Program Director, Reinert Center for Transformative Teaching and Learning, Saint Louis University

17 Followers  |  24 Following  |  1 Posts  |  Joined: 13.11.2024  |  1.5684

Latest posts by robertsplace.bsky.social on Bluesky


Catapult Grant

The funding window for ITEF’s catapult grants closes Friday!

innovteched.com/catapultgrant/

29.10.2025 13:26 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
 A step-by-step visual representation of the PEER AND AI REVIEW + REFLECTION (PAIRR) process. The graphic consists of five staggered steps, each in a hexagonal shape with a number and description: 	1.	Draft – Students create a rough draft. 	2.	Peer Feedback – Students provide and receive peer feedback. 	3.	AI Feedback – Students enter their prompt, draft, and the assignment rubric into an AI tool. 	4.	Reflect – Students complete a comparative reflection on AI and peer feedback. 	5.	Revise – Students revise.

A step-by-step visual representation of the PEER AND AI REVIEW + REFLECTION (PAIRR) process. The graphic consists of five staggered steps, each in a hexagonal shape with a number and description: 1. Draft – Students create a rough draft. 2. Peer Feedback – Students provide and receive peer feedback. 3. AI Feedback – Students enter their prompt, draft, and the assignment rubric into an AI tool. 4. Reflect – Students complete a comparative reflection on AI and peer feedback. 5. Revise – Students revise.

How can AI support rather than replace student writing and thinking? How can we encourage confidence and skepticism of AI outputs? Our approach, developed at UC Davis, combines peer review with AI feedback, emphasizing reflection and agency. 1/3

08.04.2025 17:46 β€” πŸ‘ 60    πŸ” 13    πŸ’¬ 8    πŸ“Œ 2

This sounds like an interesting approach to testing AI’s role in peer review. Appreciate the framing and transparency here and I’m curious to see how PAIRR gets implemented and assessed in these contexts.

08.04.2025 20:30 β€” πŸ‘ 2    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0
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What percentage of students are you willing to falsely accuse of cheating with AI?

There is a trade-off between false accusations and detection rates for AI. At a 10% false positive rate, detectors find 80% or less of AI content. At a 1% rate most find 60% or less.

Don’t trust AI detectors!

06.01.2025 14:30 β€” πŸ‘ 131    πŸ” 43    πŸ’¬ 4    πŸ“Œ 9
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Would your classroom AI policy survive an ethics tournament? I asked 50 students to follow a "think-pair-merge" process to distill everyone's ideas down to 4 semifinalists, resulting in some solid guidelines (and a lively debate along the way) blog.still-water.net/pooling-idea... πŸ˜β™»οΈ

12.12.2024 16:59 β€” πŸ‘ 6    πŸ” 2    πŸ’¬ 2    πŸ“Œ 0

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