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01 · Cuesta AI policy

1.1 · Three policies, clearly explained

1.2 · What is permitted in this task?

1.3 · Make AI assistance visible

1.4 · Investigate fairly

02 · How AI works

2.1 · Watch a model learn a pattern

2.2 · What fits in the context?

2.3 · Give the answer a source

2.4 · An agent can act. Set the boundary.

03 · History and the larger picture

3.1 · Early AI: Rules, Expert Systems, and Uneven Progress

3.2 · Learning from Data: Why the 2012 ImageNet Result Mattered

3.3 · Transformers, Language Models, and Public Interfaces

3.4 · The Larger Picture: Multimodal Systems, Tools, and Simulated Worlds

04 · Evaluate outputs and protect people

4.1 · Check Claims, Calculations, and Citations

4.2 · Protect Privacy, Fairness, and Access

4.3 · Read Detector Reports Without Automating Accusations

4.4 · Make and Document a Classroom Release Decision

05 · Faculty and student workflows

5.1 · Faculty workflow: draft, inspect, and revise

5.2 · Student workflow: try, request a hint, explain, and transfer

5.3 · Evidence workflow: verify claims, quotations, and citations

5.4 · Assessment workflow: preserve the outcome and provide a fair route

06 · Products and tool choices

6.1 · Read the product map before choosing

6.2 · Test the teaching task, not the sales pitch

6.3 · Check creative tools, agents, and deployment risks

6.4 · Write a defensible selection and update plan

07 · World models and emerging directions

7.1 · World Models: Predicting What Happens Next

7.2 · Plausible Images Are Not Validated Predictions

7.3 · Agents: When Predictions Lead to Actions

7.4 · A Small Classroom Investigation and an Update Habit

08 · Classroom capstone and updates

8.1 · Start the Capstone with Evidence of Learning

8.2 · Make Permission, Disclosure, and Access Explicit

8.3 · Stress-Test the Plan and Score It for Revision

8.4 · Package the Capstone and Keep It Current

Quiz

Question 1: Identify the policy layer

Question 2: Choose the correct permission category

Question 3: Separate training from inference

Question 4: Identify a grounded answer

Question 5: Check a citation

Question 6: Interpret a detector report

Question 7: Compare products responsibly

Question 8: Recognize a world-model limit

Survey/Feedback

Survey 1: Confidence with Cuesta AI policy

Survey 2: Most useful practice

Survey 3: Capstone support needed

Welcome to "Practical AI for Teaching and Learning: Cuesta Faculty Studio," a comprehensive online course designed specifically for educators at Cuesta College. As artificial intelligence continues to reshape the educational landscape, faculty members need practical, actionable strategies to integrate AI responsibly and effectively into their classrooms.

Welcome to "Practical AI for Teaching and Learning: Cuesta Faculty Studio," a comprehensive online course designed specifically for educators at Cuesta College. As artificial intelligence continues to reshape the educational landscape, faculty members need practical, actionable strategies to integrate AI responsibly and effectively into their classrooms. This course demystifies generative AI, moving beyond the hype to focus on real-world teaching applications, institutional policies, and student success.

Throughout this studio experience, you will explore the Cuesta AI policy in depth, learning how to navigate restricted, conditional, and open AI use while maintaining academic integrity. We will break down how AI actually works—from tokens and context windows to retrieval and grounding—so you can understand where these tools get their information and why they sometimes fail. You will also dive into the history of AI, evaluate outputs for accuracy and fairness, and develop robust workflows for both faculty and students.

By the end of the course, you will be equipped to evaluate AI products based on pedagogical value rather than sales pitches, understand emerging trends like world models and AI agents, and design a classroom capstone project that explicitly addresses AI permission, disclosure, and access. Whether you are looking to streamline your grading workflow, design AI-resilient assessments, or guide students in using AI as a learning partner, this course provides the foundational knowledge and hands-on practice you need to lead with confidence in the AI era.

Practical AI for Teaching and Learning: Cuesta Faculty Studio

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            <p>Artificial intelligence is fundamentally reshaping the educational landscape, presenting both unprecedented opportunities and complex challenges for educators. "Practical AI for Teaching and Learning: Cuesta Faculty Studio" is designed to equip faculty members with the foundational knowledge and practical skills necessary to navigate this rapidly evolving terrain. Rather than simply focusing on the mechanics of specific software, this course delves into the underlying mechanisms of generative AI, exploring how models process context, retrieve information, and occasionally produce inaccuracies. By understanding the history, architecture, and inherent limitations of these systems—from early expert rules to modern multimodal agents—educators can make informed, critical decisions about integrating AI into their pedagogical practices while safeguarding academic integrity, fairness, and student privacy.</p>

<p>Throughout this comprehensive studio experience, participants will translate theoretical understanding into actionable, everyday classroom strategies. The curriculum begins with a deep dive into the Cuesta College AI policy, establishing clear frameworks for restricted, conditional, and open AI use. From there, faculty will explore practical workflows for both teaching and learning, mastering how to evaluate AI outputs, verify citations, and responsibly interpret AI detector reports without relying on automated accusations. Ultimately, the course culminates in a hands-on capstone project where educators will design, stress-test, and package a defensible AI integration plan tailored to their specific teaching tasks, ensuring they remain adaptable, effective, and confident in the face of emerging technological advancements.</p>
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