Grok-Produced Summary from Responses - Framework for Good Practices for AI with Students

This framework synthesizes webinar responses on creating conditions for effective and responsible AI use in education. It is structured around three pillars: promoting positive outcomes, preventing negative outcomes, and fostering responsible AI use.

1. Promoting Positive Outcomes

Leverage AI to enhance engagement, personalize learning, and prepare students for future skills.

Increase Engagement:
- Use AI to create interactive quizzes, games, or creative projects (e.g., presentations, videos, songs) that align with students’ interests.
- Encourage students to compare AI outputs from different platforms (e.g., ChatGPT vs. Gemini) to foster critical analysis and discussion.
- Allow students to co-create AI-powered activities or share how they use AI tools, promoting ownership and excitement.
- Match AI tasks to real-world applications, like composing resumes or pursuing interest-driven research.

Enable Personalized Learning:
- Use AI to tailor content to students’ reading levels, languages, or learning needs (e.g., generating summaries, practice quizzes, or explanations).
- Encourage students to refine AI prompts to customize outputs, fostering prompt engineering skills.
- Provide AI as a personal tutor for iterative feedback on writing, math, or other subjects, allowing students to revise and learn at their own pace.
- Offer flexible activity options and accommodations to support diverse learners.

Support Skill Preparation:
- Teach students to use AI for step-by-step processes (e.g., math problem-solving, research strategies) to build foundational skills.
- Design tasks that develop communication, collaboration, creativity, and digital literacy through AI use.
- Use AI to prepare students for tests (e.g., SAT) or create enrichment activities to address skill gaps.
- Guide students in crafting and evaluating prompts to enhance questioning and problem-solving skills.

Provide 24/7 Learning Support:
- Integrate AI chatbots or tools into learning management systems for instant access to explanations or feedback.
- Encourage students to use AI to clarify concepts, summarize notes, or identify knowledge gaps at any time.
- Provide guides for responsible AI use across devices, ensuring accessibility at home and school.

Foster Agentic Learning:
- Involve students in setting learning goals, co-developing success criteria, and choosing how to demonstrate understanding.
- Encourage independent problem-solving by having students design prompts, propose projects, or map out learning goals.
- Create a classroom culture that embraces risk-taking, feedback, and reflection on AI use.

Enhance Generative Teaching:
- Use AI to generate lesson ideas, differentiated activities, or formative data analysis to meet diverse student needs.
- Create tiered tasks or language supports based on students’ levels or accommodations (e.g., IEPs/504 plans).
- Model lifelong learning by reflecting on AI’s role in teaching and experimenting with prompt formulation.

2. Preventing Negative Outcomes

Address concerns about cheating, loss of critical thinking, information literacy, and authentic learning.

Mitigate Cheating and Uphold Academic Integrity:
- Define clear guidelines for when and how AI can be used in assignments, emphasizing transparency (e.g., declare AI use, submit prompts).
- Focus assessments on the learning process (e.g., reflections, drafts, oral defenses) rather than just the final product.
- Redesign assignments to prioritize open-ended discussions, in-class writing, or tasks AI cannot easily complete.
- Teach the value of learning and curiosity, reducing the incentive to cheat by fostering engagement and growth over perfection.
- Use oral exams, presentations, or process-focused tasks (e.g., annotated bibliographies, scaffolding) to verify student understanding.

Preserve Critical Thinking, Reasoning, and Writing Skills:
- Embed critical thinking across the curriculum by having students analyze, critique, or edit AI-generated outputs for errors or biases.
- Require students to explain their reasoning, processes, or prompt strategies in writing, orally, or through projects.
- Incorporate tactile, in-class, or non-AI activities (e.g., handwritten essays, group discussions) to reinforce foundational skills.
- Teach metacognition and AI literacy, helping students reflect on how AI influences their thinking and how to use it as a tool, not a replacement.
- Design open-ended assignments that encourage reflection, process writing, or application of learning to new contexts.

Strengthen Information Literacy:
- Teach students to verify AI outputs by cross-checking with reputable sources (e.g., academic journals, library databases).
- Provide structured lessons on evaluating credibility, bias, and authorship of AI-generated content, including discussions on hallucinations and algorithmic bias.
- Involve librarians to integrate information literacy across disciplines, teaching students to prompt AI for sources and analyze their validity.
- Use activities like comparing AI responses to traditional research or tracking AI citations to build critical evaluation skills.
- Embed AI literacy as part of digital literacy, addressing how AI is trained and its limitations.

Ensure Authentic Learning:
- Design assignments that require personal opinions, creativity, or real-world application (e.g., experiential projects, hands-on tasks).
- Test assignments to ensure AI cannot easily complete them, focusing on processes like planning, drafts, or reflections.
- Encourage collaborative learning, group discussions, or peer reviews to emphasize human interaction and idea-sharing.
- Build time for students to reflect on what they learned, how AI influenced their understanding, and what they still wonder.
- Align AI use with learning goals, ensuring technology supports, rather than replaces, authentic engagement with content.

3. Fostering Responsible AI Use

Create a culture of transparency, reflection, and ethical AI integration.

Promote AI Literacy and Transparency:
- Educate students on how AI works, its strengths, weaknesses, and potential biases, using real-time demonstrations (e.g., analyzing AI prompts in class).
- Model responsible AI use by openly acknowledging when and how educators use AI (e.g., drafting syllabi, generating ideas).
- Encourage students to document their AI use (e.g., submit prompts, compare AI outputs to their work) to build accountability.

Encourage Reflective and Ethical Practices:
- Integrate reflection activities where students assess how AI helped or hindered their learning and how they could improve their prompts.
- Discuss ethical issues, academic integrity policies, and the societal implications of AI use (e.g., dependency, privacy).
- Foster a growth mindset by normalizing mistakes and emphasizing learning through struggle, not just AI-generated answers.

Balance AI and Human Interaction:
- Limit over-reliance on AI by incorporating in-class, collaborative, or tactile activities that prioritize human connection.
- Use AI as a thinking partner or mentor model, encouraging students to paraphrase, critique, or build on AI outputs rather than copying them.
- Maintain personal engagement with students through discussions, feedback, and conversations to understand their challenges and progress.

Support Faculty and Institutional Collaboration:
- Provide professional development on AI literacy, prompt engineering, and integrating AI into teaching workflows.
- Collaborate with librarians to embed information literacy and AI literacy into the curriculum.
- Develop clear institutional policies on AI use, including acceptable behaviors, consequences, and guidelines for assignments.

Implementation Considerations

Start Small: Begin with low-stakes AI tasks (e.g., brainstorming, summarizing) to build student and teacher confidence.
Iterate and Reflect: Regularly assess how AI impacts learning outcomes and adjust strategies based on student feedback and performance.
Ensure Equity: Provide universal access to AI tools and training to avoid disparities in technology access or skills.
Model Lifelong Learning: Teachers should experiment with AI, share their learning process, and demonstrate adaptability to new tools.

This framework balances excitement about AI’s potential with proactive strategies to address risks, ensuring students use AI responsibly while developing essential skills for the future.

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