Embedded Files
The "What"
Steps to Research Jigsaw
Steps to Research Jigsaw
(with AI as your partner)
(with AI as your partner)
Your Goal: Use AI to get to the "good stuff" of these resources to fuel our conversation.
Instructions:
Select the theme that most interests you.
Gather with others interested in that theme to form a small group.
Choose one resource from the theme.
Summarize the resource with an AI Tool.
Open ChatGPT, Perplexity, Claude, or your favorite AI tool.
Use a prompt like, "Summarize the key arguments of this article [paste link or text]" or "Explain Bloom's 2-Sigma Problem to a K-12 teacher."
Discuss the findings with your group. What is the main "a-ha" or "oh-no"? Critique the AI summary.
Decide to post findings in the Dueling AIs? Research Jigsaw Collaboration Slides
Be ready to share your group's key takeaway with the whole group.
Consider one concrete, actionable solution OR one core, guiding principle
Research Jigsaw Collaborative BoardTheme 1
Theme 1
The "Cheating" Problem & Student Perspectives
The "Cheating" Problem & Student Perspectives
Choose this theme if you're focused on the immediate challenge of academic integrity and what students are actually doing.
Article: What do AI chatbots really mean for students and cheating?
Source: Stanford Graduate School of Education
Why This One? This is a great, high-level overview of the "cheating" panic. It provides recent data on student behavior and reframes the conversation around why students cheat in the first place.
Related Research
Cheating in the age of generative AI: A high school survey study of cheating behaviors before and after the release of ChatGPT.pdfCheating in the Age of Generative AI - Stanford
Theme 2
Theme 2
The "AI Tutor" Debate (Theory vs. Practice)
The "AI Tutor" Debate (Theory vs. Practice)
Choose this theme if you're interested in the foundational theories of AI in education—and their limitations.
Article 1 (Theory): Two-Sigma Tutoring: Separating Science Fiction from Science Fact
Source: Education Next
Why This One? This article explains the 1984 "two-sigma problem," the famous study showing that 1-on-1 human tutoring yields massive learning gains. It explores the core goal of AI: to replicate this success at scale.
Article 2 (Practice): AI Tutors Can't Solve Bloom's Two Sigma Problem
Source: Josh Brake (Substack)
Why This One? This is a direct rebuttal to the hype. It argues that AI tutors miss the essential human elements (motivation, relationship, care) that actually make tutoring work. (This is a great one to pair with Article 1).
Related Research
bloom-two-sigma.pdfBloom's 2-Sigma Problem
-Original 1984-
Theme 3
Theme 3
A Design Solution (AI-Resilient Assessment)
A Design Solution (AI-Resilient Assessment)
Choose this theme if you want to skip the "why" and get straight to the "what do I do on Monday?"
Article: 4 Steps to Design an AI-Resilient Learning Experience
Source: MIT Sloan Teaching & Learning Technologies
Why This One? This is a practical, step-by-step guide for redesigning your assignments. It focuses on process, unique application, and making thinking visible—all of which are perfectly aligned with your session goals.
Related Resources
TII_GL_AI_Research_EduFocusedSurvey_Ebook_0425.pdfCrossroads: Navigating the Intersection of AI in Education - Turnitin
Reassessing academic integrity in the age of AI: A systematic literature review on AI and academic integrity.pdfReassessing Academic Integrity in the Age of AI
Page updated
Report abuse