Yaneth Moreno

Trusting AI is not losing control. The TRUST method (Transparency, Relevance, User Control, Safety, Tracking) helps me evaluate tools before using them. Independent AI needs weekly oversight. I am still responsible.

I will evaluate one tool using TRUST this week. I will set a 15-minute weekly reminder to review interactions and log errors. I will complete my AI Growth Plan.

I learned that AI is not just for quick tasks like creating quizzes. It can also be a thinking partner for complex, long-term projects, such as redesigning a simulation or a final project. The CRAFT method (Context, Request, Audience, Format, and Tone) gave me a clear structure to communicate better with AI. I also understood that evaluating AI outputs is key: I need to check technical accuracy, appropriateness for my students, and the professional standards of my field. If I wouldn't put my name on the result, it's not ready.

This week I will choose a teaching challenge I've been… >>>

AI is an assistant, not a replacement. The three questions (harm? my expertise? routine?) help me decide what to delegate. If I spend more time fixing than creating, it's not working.

This week I'll delegate one routine, low-risk task (like a vocabulary list). Safety decisions, grades, and empathetic feedback stay with me. I'll measure whether I actually save time without losing quality.

This module gave me a new way to communicate AI concepts to others. The apprentice analogy and the Tell–Team–Trust framework simplify complex ideas without losing technical accuracy. It reminded me that AI literacy isn't just about algorithms—it's about knowing when to direct, collaborate, or delegate, and always grounding use in responsibility.

I'll use the Tell–Team–Trust framework with my students to help them think strategically about AI deployment, not just code models. I'll also integrate the three pillars into my teaching—moving beyond technical instruction to include responsible use and practical judgment—so my students graduate as both builders and thoughtful users of… >>>

I take away the idea of not banning ChatGPT, but rather teaching students to use it with critical thinking. I will have my students compare its responses with reliable sources and reflect on the differences.

 I learned that ChatGPT can be a powerful virtual tutor, especially in large classrooms where one-on-one attention is limited. It can personalize learning and help students who need extra support. However, I also learned about the risks: overreliance on AI can reduce critical thinking, and ChatGPT lacks emotional intelligence and true contextual understanding.

I intend to apply this by using ChatGPT as a supplementary tool, not a replacement for my teaching. I will design activities where students first think independently, then use ChatGPT to check or expand their ideas. I also plan to teach my students about academic integrity and… >>>

Having worked with AI, I'm aware of its capabilities and limitations. What this course made me reflect on is not whether ChatGPT can be used in education, but how to redesign assessments and teaching methods so students learn with AI, not just copy from it. The real challenge is pedagogical, not technological.

This course effectively breaks down online learner engagement into two critical, interconnected pillars:

1. Social Engagement: This is the foundation of building a learning community. It's not a bonus; it's essential for success. Key takeaways include:
   • Proactive Connection is Key: The instructor and support staff making contact before the course starts (welcome email/video, check-in from admissions or career services) sets a tone of support and dramatically increases a student's comfort level.
   • Multi-Point Contact: Engagement must be fostered between Instructor-to-Student (reliable, multi-channel contact info), Student-to-Student (intro activities, ongoing sharing spaces), and Staff-to-Student (showing the full support network).
   • Mimicking the On-Ground Dynamic: We
   … >>>

I learned that the core difference is that games focus on goals, points, and winning, while simulations focus on modeling reality to practice decision-making and understand cause-effect in a safe environment. Both are tools for learning by doing.

How I’ll apply it:
In my simulation course for engineering students, I won’t just explain system theory—I’ll have students interact with a real-time process simulator where they adjust inputs (like flow rate, temperature, or load) and immediately see how the virtual system responds. The goal won’t be to “win,” but to experiment, observe outcomes, and optimize performance through trial and error.

Question… >>>

Considering Heineke and Meile's (2000) criteria—especially the 'aha! effect' and having students 'generate data'—how can we design or select a game or simulation that balances the realism necessary for a meaningful simulation with the fun and low-stress environment required for an effective educational game?

Could you provide a concrete example of an activity that achieves this balance in an online course?