daBongo LMS AI Training Courses

Lesson Content

Audio workflows require listening-based QA: pronunciation, pacing, noise, emotional tone, volume, and brand suitability. Students should never treat first-generation audio as finished.

Student task scenario 1: Create a short script with pronunciation notes for technical terms. Student task help: Use pretend, public, or low-risk practice material. Copying the first AI answer into a text editor means pasting it into Notepad, Word, or another notes file so you can compare it with your revised answer. A clarification prompt is a short follow-up that tells the AI what to fix, add, remove, or explain. Example clarification prompt: "Make this easier for a beginner, add one concrete example, and show the next three steps as a checklist."

Student task scenario 2: Review an audio draft and write revision commands for pacing and emphasis. Student task help: Use pretend, public, or low-risk practice material. Copying the first AI answer into a text editor means pasting it into Notepad, Word, or another notes file so you can compare it with your revised answer. A clarification prompt is a short follow-up that tells the AI what to fix, add, remove, or explain. Example clarification prompt: "Make this easier for a beginner, add one concrete example, and show the next three steps as a checklist."

Troubleshooting: When a command creates polished but inaccurate output, switch from creation mode to review mode. Ask it to list assumptions, uncertain claims, missing inputs, and risks. When media or file tools are involved, confirm licensing, export format, accessibility, and brand constraints before publication.

Quality Rubric:

• Each scenario has a concrete input and output.
• The student keeps the first output and revised output for comparison.
• The student can explain which command pattern worked best and why.
• The workflow includes a privacy and verification checkpoint.