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Educational Modules & Artifacts

Module 1: Prompting Foundations

Explore the fundamental principles of prompt engineering, including persona assignment and iterative refinement for pedagogical applications.

Module 2: Ethics & Accuracy

Analyzing the ethical dimensions of AI in education, focusing on hallucination detection and bias mitigation in automated artifacts.

Module 3: Advanced Frameworks

A deep dive into cross-platform integration and technical infrastructure optimization for large-scale educational utilities.

Advanced Strategies for Prompting and AI Frameworks

Mastering interaction with intelligent agents is essential for contemporary efficiency. This module examines linguistic engineering techniques to create precise instructions that ensure reliable and ethical results. You will explore automation infrastructure and learn to optimize productivity while maintaining rigorous quality standards. For inquiries, contact dbengts2@hgtc.edu.

Artifact Download

Additional Practice Artifact

 Module 1 Prompting Practice – Email Revision

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  • Original Prompt: "Write an email to my manager asking for Friday off."
     

  • Revised Prompt: "Act as a professional employee. Write a polite and concise email to my manager requesting time off for this Friday. Mention that all my current projects are up to date and that I have asked Sarah to cover any urgent client requests."

Module 1 Assignment Commentary – Task and Prompt Revision Summary

For the Module 1 artifact, I developed a study plan for CPT-128 to better manage my academic and professional responsibilities. Initial attempts were unsuccessful, as a vague prompt resulted in a generic one-week schedule lacking pedagogical depth. To optimize the output, I introduced a specialized persona—a professional educator focused on neurodiversity—and requested specific adult learning strategies in a structured table format. This approach significantly improved the results, yielding a comprehensive term-long schedule with actionable study guidelines. Despite this progress, human oversight remained critical; the AI misaligned calendar dates with source documents, requiring manual correction. This exercise demonstrates that while sophisticated prompting enhances structural quality, rigorous verification is necessary to ensure factual integrity.

Checkpoint 1: Commentary

In this practice exercise, I improved a basic prompt for a workplace time-off request. By assigning the AI a specific persona ("professional employee") and providing contextual details—such as project status and coverage plans—I successfully shifted the output from a blunt message to a professional, considerate draft. While the AI streamlined the formatting and tone, human oversight remained necessary to finalize placeholders and ensure the sign-off matched my personal voice. This artifact illustrates a progression from basic zero-shot prompting to a sophisticated approach using persona-driven constraints and detailed context for high-quality results.

Progress Reflection

During this module, I discovered that while AI excels at organizing data and drafting content, it requires constant human oversight due to frequent errors in contextual accuracy. My prompting strategy has evolved from simple requests to structured frameworks that include specific personas, target audiences, and source document integration. This approach significantly improves document structure but still necessitates rigorous verification. For instance, in my CPT-128 study plan, the AI created an impressive table that failed to correctly align with calendar dates from the source material. Without manual correction, the output would have been unusable. Currently, I find AI most effective for brainstorming and administrative formatting, whereas tasking it with precise factual data remains a high-risk endeavor. Moving forward, my primary focus will be maintaining human judgment as the final filter, ensuring all AI-generated facts are verified against primary sources.

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