Managing sensitive data in Storyline simulations, including AI-assisted workflows
Our source systems may contain confidential information that can't appear in simulations. How are others handling this? Synthetic/test data before recording? Redaction or replacement after capture? Edited screenshots instead of recordings? AI-assisted redaction, data replacement, or generation of realistic synthetic data? We're looking for a workflow that balances security, realism, efficiency, and maintainability.I turned my course QA checklist into a free Claude skill. What would you add?
I started this checklist in my master's program, and most of it was accessibility. Over the years I kept adding the things I actually catch when I review a course: activities that don't match the stated outcomes, quiz feedback that only says "incorrect, try again," screenshots of a UI that changed two releases ago. The checklist worked great, but was manual. Recently I turned it into a Claude skill that checks 53 UX & LX criteria. You give it an exported course or a PowerPoint deck and it gives you back a checklist to validate, not a verdict. It answers what it can from the files and drafts an answer when it isn't sure. Anything it can't check, like keyboard navigation or how a screen reader sounds, it leaves open for you. Each finding gets a severity level based on how it affects the learner (blocked, inaccurate, adds effort, and so on), so you know what has to be fixed before launch and what can wait for the next revision. It runs in the Claude desktop app or claude.ai with code execution turned on, so you don't need to install anything technical. It's been tested on a Mindsmith.ai course export on a Windows machine. If it doesn't recognize your export, it'll tell you and ask before trying, and I'd ✨love ✨ to hear how it handles Rise, Storyline or anything else. It's free, and there's a sample report you can click through before trying it: https://chickadee368.github.io/learner-first-qa/ I'd really like to hear from people who QA courses for a living. What do you check that isn't on the list? And if you run it on one of your own exports, I'd love to know where it got things wrong! 🔗 to the overview: https://chickadee368.github.io/learner-first-qa/ 🔗 to the repo: https://github.com/chickadee368/learner-first-qaRise 360 AI Audio changing volume block to block
Two fixes that seem to work for me: Quickest: Edit AI Audio, advanced sound settings, change to V3, change stability to max, regenerate. Longest: Copy the script to another block with working loud volume, generate the audio there, insert it, duplicate block, convert content into correct block format, copy in content. Remove audio from block used and replace with correct text.Best practices for maintaining a large library of Storyline system simulations
We’re exploring Storyline for building a library of software simulations, including processes that move between multiple systems that share data. For teams doing this at scale: How do you structure simulations for easier maintenance when applications change? Do you use screen recordings, screenshots, custom-built interactions, or a hybrid? What reusable templates/components have worked well? Are you using AI to identify UI changes, update simulations, or reduce maintenance effort? We’re particularly interested in approaches that remain manageable as the simulation library grows.AI Tool for creating conversations
Hi everyone, I'm exploring the possibility of using text between 2 (or more) people to create an AI-generated audio conversation, in most cases between a CSR and customer. From my web search I see there's a utility called Musely that might work but my company's internet policies block me from seeing the page. So, I figured I'd poll this wonderful group of creators to see what they may know or could recommend. Thanks!Discover the latest Articulate 360 features
New training formats, agentic AI, expanded integrations, and more! Join David Anderson, Director of Training, on October 20th at 11 a.m. ET for a full tour of what’s new and learn how to start using the reimagined platform. You’ll learn how to: Create faster with our reimagined dashboard. Use new Nova capabilities like AI Avatars. Turn existing docs into training kits, instantly. And more! REGISTER HEREHow are you designing courses for localization from the beginning?
I've been thinking a lot about localization as a design decision rather than something that happens after a course is built. One thing I've learned from working on global learning projects is that decisions made early, including how text is handled in graphics, how media is structured, how reviews are managed, and how the course is packaged, can make a huge difference once you begin scaling across languages. I'm curious how others approach this. What are you doing during the design and development stage to make localization easier later?
